Overview

Brought to you by YData

Dataset statistics

Number of variables223
Number of observations2361465
Missing cells366711980
Missing cells (%)69.6%
Total size in memory3.9 GiB
Average record size in memory1.7 KiB

Variable types

Numeric19
Unsupported99
Text104
Boolean1

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
datasetName has constant value "NMNH Extant Biology" Constant
eventType has constant value "Baffin Island" Constant
samplingEffort has constant value "67.0" Constant
fieldNotes has constant value "-63.0" Constant
municipality has constant value "-53.33" Constant
earliestEraOrLowestErathem has constant value "Plantae" Constant
latestEraOrHighestErathem has constant value "Tracheophyta" Constant
earliestPeriodOrLowestSystem has constant value "Magnoliopsida" Constant
earliestEpochOrLowestSeries has constant value "5410907.0" Constant
lowestBiostratigraphicZone has constant value "Scharf, U." Constant
member has constant value "coronata" Constant
dateIdentified has constant value "Asterales" Constant
identificationReferences has constant value "Guatteria punctata (Aubl.) R.A.Howard" Constant
identificationRemarks has constant value "US" Constant
scientificNameID has constant value "69.0" Constant
parentNameUsageID has constant value "Campanula" Constant
originalNameUsageID has constant value "Plantae, Dicotyledonae (basal), Magnoliales, Annonaceae, Annonoideae" Constant
nameAccordingToID has constant value "Plantae" Constant
nameAccordingTo has constant value "6.0" Constant
superfamily has constant value "Miconia coronata" Constant
subgenusKey has constant value "NE" Constant
typifiedName has constant value "French Guiana" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
accessRights has 2361465 (100.0%) missing values Missing
bibliographicCitation has 2361465 (100.0%) missing values Missing
language has 2361465 (100.0%) missing values Missing
references has 2361465 (100.0%) missing values Missing
rightsHolder has 2361465 (100.0%) missing values Missing
type has 2361465 (100.0%) missing values Missing
datasetID has 2361465 (100.0%) missing values Missing
ownerInstitutionCode has 2361465 (100.0%) missing values Missing
informationWithheld has 2361465 (100.0%) missing values Missing
dataGeneralizations has 2361465 (100.0%) missing values Missing
dynamicProperties has 2361465 (100.0%) missing values Missing
catalogNumber has 213211 (9.0%) missing values Missing
recordNumber has 1045436 (44.3%) missing values Missing
recordedBy has 498671 (21.1%) missing values Missing
recordedByID has 2361465 (100.0%) missing values Missing
organismQuantity has 2361465 (100.0%) missing values Missing
organismQuantityType has 2361465 (100.0%) missing values Missing
sex has 2009605 (85.1%) missing values Missing
lifeStage has 2107141 (89.2%) missing values Missing
reproductiveCondition has 2361465 (100.0%) missing values Missing
caste has 2361465 (100.0%) missing values Missing
behavior has 2361465 (100.0%) missing values Missing
vitality has 2361465 (100.0%) missing values Missing
establishmentMeans has 2361465 (100.0%) missing values Missing
degreeOfEstablishment has 2361465 (100.0%) missing values Missing
pathway has 2361465 (100.0%) missing values Missing
georeferenceVerificationStatus has 2361465 (100.0%) missing values Missing
preparations has 1223403 (51.8%) missing values Missing
disposition has 2361465 (100.0%) missing values Missing
associatedOccurrences has 2361465 (100.0%) missing values Missing
associatedReferences has 2361465 (100.0%) missing values Missing
associatedSequences has 2358364 (99.9%) missing values Missing
associatedTaxa has 2361465 (100.0%) missing values Missing
otherCatalogNumbers has 2361465 (100.0%) missing values Missing
occurrenceRemarks has 2047567 (86.7%) missing values Missing
organismID has 2361465 (100.0%) missing values Missing
organismName has 2361465 (100.0%) missing values Missing
organismScope has 2361465 (100.0%) missing values Missing
associatedOrganisms has 2361465 (100.0%) missing values Missing
previousIdentifications has 2361465 (100.0%) missing values Missing
organismRemarks has 2361465 (100.0%) missing values Missing
materialEntityID has 2361465 (100.0%) missing values Missing
materialEntityRemarks has 2361465 (100.0%) missing values Missing
verbatimLabel has 2361463 (> 99.9%) missing values Missing
materialSampleID has 2361463 (> 99.9%) missing values Missing
eventID has 2361465 (100.0%) missing values Missing
parentEventID has 2361465 (100.0%) missing values Missing
eventType has 2361464 (> 99.9%) missing values Missing
fieldNumber has 2164707 (91.7%) missing values Missing
eventDate has 419645 (17.8%) missing values Missing
eventTime has 2361465 (100.0%) missing values Missing
startDayOfYear has 669488 (28.4%) missing values Missing
endDayOfYear has 669487 (28.4%) missing values Missing
year has 423103 (17.9%) missing values Missing
month has 542651 (23.0%) missing values Missing
day has 762156 (32.3%) missing values Missing
verbatimEventDate has 1255734 (53.2%) missing values Missing
habitat has 2177638 (92.2%) missing values Missing
samplingProtocol has 2361465 (100.0%) missing values Missing
sampleSizeValue has 2361465 (100.0%) missing values Missing
sampleSizeUnit has 2361465 (100.0%) missing values Missing
samplingEffort has 2361464 (> 99.9%) missing values Missing
fieldNotes has 2361464 (> 99.9%) missing values Missing
eventRemarks has 2361465 (100.0%) missing values Missing
locationID has 2084504 (88.3%) missing values Missing
higherGeographyID has 2361465 (100.0%) missing values Missing
higherGeography has 73521 (3.1%) missing values Missing
continent has 411635 (17.4%) missing values Missing
waterBody has 1923752 (81.5%) missing values Missing
islandGroup has 2309211 (97.8%) missing values Missing
island has 2204394 (93.3%) missing values Missing
countryCode has 95309 (4.0%) missing values Missing
stateProvince has 637063 (27.0%) missing values Missing
county has 1825427 (77.3%) missing values Missing
municipality has 2361464 (> 99.9%) missing values Missing
locality has 337166 (14.3%) missing values Missing
verbatimLocality has 2361465 (100.0%) missing values Missing
verbatimElevation has 2293080 (97.1%) missing values Missing
verticalDatum has 2361465 (100.0%) missing values Missing
verbatimDepth has 2346998 (99.4%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 2361465 (100.0%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 2361465 (100.0%) missing values Missing
locationAccordingTo has 2361465 (100.0%) missing values Missing
locationRemarks has 2361465 (100.0%) missing values Missing
decimalLatitude has 1649758 (69.9%) missing values Missing
decimalLongitude has 1649758 (69.9%) missing values Missing
coordinateUncertaintyInMeters has 2318343 (98.2%) missing values Missing
coordinatePrecision has 2361465 (100.0%) missing values Missing
pointRadiusSpatialFit has 2361463 (> 99.9%) missing values Missing
verbatimCoordinateSystem has 2103311 (89.1%) missing values Missing
verbatimSRS has 2361465 (100.0%) missing values Missing
footprintWKT has 2361465 (100.0%) missing values Missing
footprintSRS has 2361465 (100.0%) missing values Missing
footprintSpatialFit has 2361465 (100.0%) missing values Missing
georeferencedBy has 2361463 (> 99.9%) missing values Missing
georeferencedDate has 2361465 (100.0%) missing values Missing
georeferenceProtocol has 2055864 (87.1%) missing values Missing
georeferenceSources has 2361465 (100.0%) missing values Missing
georeferenceRemarks has 2309420 (97.8%) missing values Missing
geologicalContextID has 2361465 (100.0%) missing values Missing
earliestEonOrLowestEonothem has 2361465 (100.0%) missing values Missing
latestEonOrHighestEonothem has 2361463 (> 99.9%) missing values Missing
earliestEraOrLowestErathem has 2361463 (> 99.9%) missing values Missing
latestEraOrHighestErathem has 2361463 (> 99.9%) missing values Missing
earliestPeriodOrLowestSystem has 2361463 (> 99.9%) missing values Missing
latestPeriodOrHighestSystem has 2361463 (> 99.9%) missing values Missing
earliestEpochOrLowestSeries has 2361464 (> 99.9%) missing values Missing
latestEpochOrHighestSeries has 2361463 (> 99.9%) missing values Missing
earliestAgeOrLowestStage has 2361465 (100.0%) missing values Missing
latestAgeOrHighestStage has 2361465 (100.0%) missing values Missing
lowestBiostratigraphicZone has 2361464 (> 99.9%) missing values Missing
highestBiostratigraphicZone has 2361463 (> 99.9%) missing values Missing
lithostratigraphicTerms has 2361462 (> 99.9%) missing values Missing
group has 2361465 (100.0%) missing values Missing
formation has 2361465 (100.0%) missing values Missing
member has 2361464 (> 99.9%) missing values Missing
bed has 2361465 (100.0%) missing values Missing
identificationID has 2361465 (100.0%) missing values Missing
verbatimIdentification has 2361462 (> 99.9%) missing values Missing
identificationQualifier has 2352466 (99.6%) missing values Missing
typeStatus has 2274518 (96.3%) missing values Missing
identifiedBy has 1955398 (82.8%) missing values Missing
identifiedByID has 2361462 (> 99.9%) missing values Missing
dateIdentified has 2361464 (> 99.9%) missing values Missing
identificationReferences has 2361464 (> 99.9%) missing values Missing
identificationVerificationStatus has 2361462 (> 99.9%) missing values Missing
identificationRemarks has 2361463 (> 99.9%) missing values Missing
taxonID has 2361463 (> 99.9%) missing values Missing
scientificNameID has 2361464 (> 99.9%) missing values Missing
parentNameUsageID has 2361464 (> 99.9%) missing values Missing
originalNameUsageID has 2361464 (> 99.9%) missing values Missing
nameAccordingToID has 2361464 (> 99.9%) missing values Missing
namePublishedInID has 2361461 (> 99.9%) missing values Missing
taxonConceptID has 2361463 (> 99.9%) missing values Missing
acceptedNameUsage has 2361462 (> 99.9%) missing values Missing
parentNameUsage has 2361462 (> 99.9%) missing values Missing
originalNameUsage has 2361463 (> 99.9%) missing values Missing
nameAccordingTo has 2361463 (> 99.9%) missing values Missing
namePublishedIn has 2361462 (> 99.9%) missing values Missing
namePublishedInYear has 2361462 (> 99.9%) missing values Missing
class has 138555 (5.9%) missing values Missing
order has 145721 (6.2%) missing values Missing
superfamily has 2361464 (> 99.9%) missing values Missing
family has 52489 (2.2%) missing values Missing
subfamily has 2361463 (> 99.9%) missing values Missing
tribe has 2361465 (100.0%) missing values Missing
subtribe has 2361462 (> 99.9%) missing values Missing
genus has 120644 (5.1%) missing values Missing
genericName has 120736 (5.1%) missing values Missing
subgenus has 2361462 (> 99.9%) missing values Missing
infragenericEpithet has 2361463 (> 99.9%) missing values Missing
specificEpithet has 306537 (13.0%) missing values Missing
infraspecificEpithet has 2138634 (90.6%) missing values Missing
cultivarEpithet has 2361462 (> 99.9%) missing values Missing
verbatimTaxonRank has 2361463 (> 99.9%) missing values Missing
vernacularName has 2361463 (> 99.9%) missing values Missing
nomenclaturalCode has 2361463 (> 99.9%) missing values Missing
nomenclaturalStatus has 2361462 (> 99.9%) missing values Missing
taxonRemarks has 2361462 (> 99.9%) missing values Missing
elevation has 1813932 (76.8%) missing values Missing
elevationAccuracy has 2160161 (91.5%) missing values Missing
depth has 2098482 (88.9%) missing values Missing
depthAccuracy has 2120412 (89.8%) missing values Missing
distanceFromCentroidInMeters has 2356823 (99.8%) missing values Missing
mediaType has 863240 (36.6%) missing values Missing
classKey has 138556 (5.9%) missing values Missing
orderKey has 145721 (6.2%) missing values Missing
familyKey has 52491 (2.2%) missing values Missing
genusKey has 120648 (5.1%) missing values Missing
subgenusKey has 2361464 (> 99.9%) missing values Missing
speciesKey has 306496 (13.0%) missing values Missing
species has 306496 (13.0%) missing values Missing
verbatimScientificName has 94299 (4.0%) missing values Missing
typifiedName has 2361464 (> 99.9%) missing values Missing
repatriated has 92306 (3.9%) missing values Missing
relativeOrganismQuantity has 2361465 (100.0%) missing values Missing
projectId has 2361465 (100.0%) missing values Missing
gbifRegion has 114367 (4.8%) missing values Missing
level0Gid has 1911127 (80.9%) missing values Missing
level0Name has 1911127 (80.9%) missing values Missing
level1Gid has 1912765 (81.0%) missing values Missing
level1Name has 1912765 (81.0%) missing values Missing
level2Gid has 1927745 (81.6%) missing values Missing
level2Name has 1927843 (81.6%) missing values Missing
level3Gid has 2259566 (95.7%) missing values Missing
level3Name has 2260777 (95.7%) missing values Missing
iucnRedListCategory has 383088 (16.2%) missing values Missing
individualCount is highly skewed (γ1 = 350.7736071) Skewed
coordinateUncertaintyInMeters is highly skewed (γ1 = 35.60903197) Skewed
gbifID has unique values Unique
occurrenceID has unique values Unique
accessRights is an unsupported type, check if it needs cleaning or further analysis Unsupported
bibliographicCitation is an unsupported type, check if it needs cleaning or further analysis Unsupported
language is an unsupported type, check if it needs cleaning or further analysis Unsupported
references is an unsupported type, check if it needs cleaning or further analysis Unsupported
rightsHolder is an unsupported type, check if it needs cleaning or further analysis Unsupported
type is an unsupported type, check if it needs cleaning or further analysis Unsupported
datasetID is an unsupported type, check if it needs cleaning or further analysis Unsupported
ownerInstitutionCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
informationWithheld is an unsupported type, check if it needs cleaning or further analysis Unsupported
dataGeneralizations is an unsupported type, check if it needs cleaning or further analysis Unsupported
dynamicProperties is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantityType is an unsupported type, check if it needs cleaning or further analysis Unsupported
reproductiveCondition is an unsupported type, check if it needs cleaning or further analysis Unsupported
caste is an unsupported type, check if it needs cleaning or further analysis Unsupported
behavior is an unsupported type, check if it needs cleaning or further analysis Unsupported
vitality is an unsupported type, check if it needs cleaning or further analysis Unsupported
establishmentMeans is an unsupported type, check if it needs cleaning or further analysis Unsupported
degreeOfEstablishment is an unsupported type, check if it needs cleaning or further analysis Unsupported
pathway is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
disposition is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOccurrences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedTaxa is an unsupported type, check if it needs cleaning or further analysis Unsupported
otherCatalogNumbers is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismName is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismScope is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOrganisms is an unsupported type, check if it needs cleaning or further analysis Unsupported
previousIdentifications is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityID is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLabel is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialSampleID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentEventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventTime is an unsupported type, check if it needs cleaning or further analysis Unsupported
endDayOfYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
day is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingProtocol is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeValue is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeUnit is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
higherGeographyID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLocality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verticalDatum is an unsupported type, check if it needs cleaning or further analysis Unsupported
minimumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
maximumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinatePrecision is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintWKT is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceSources is an unsupported type, check if it needs cleaning or further analysis Unsupported
geologicalContextID is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEonOrLowestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestAgeOrLowestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestAgeOrHighestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
group is an unsupported type, check if it needs cleaning or further analysis Unsupported
formation is an unsupported type, check if it needs cleaning or further analysis Unsupported
bed is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimIdentification is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedIn is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
tribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
infragenericEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
cultivarEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimTaxonRank is an unsupported type, check if it needs cleaning or further analysis Unsupported
vernacularName is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
elevation is an unsupported type, check if it needs cleaning or further analysis Unsupported
elevationAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
depth is an unsupported type, check if it needs cleaning or further analysis Unsupported
depthAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
hasCoordinate is an unsupported type, check if it needs cleaning or further analysis Unsupported
hasGeospatialIssues is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedTaxonKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
phylumKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
classKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
orderKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
familyKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
speciesKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
repatriated is an unsupported type, check if it needs cleaning or further analysis Unsupported
relativeOrganismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
projectId is an unsupported type, check if it needs cleaning or further analysis Unsupported
isSequenced is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2024-12-30 22:01:58.961762
Analysis finished2024-12-30 22:03:30.431840
Duration1 minute and 31.47 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Real number (ℝ)

Unique 

Distinct2361465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1734867073
Minimum1317202451
Maximum4987328283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:30.729017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1317202451
5-th percentile1317693766
Q11319581542
median1321865964
Q31852107985
95-th percentile3467200989
Maximum4987328283
Range3670125832
Interquartile range (IQR)532526443

Descriptive statistics

Standard deviation724056043.4
Coefficient of variation (CV)0.4173553436
Kurtosis3.567878808
Mean1734867073
Median Absolute Deviation (MAD)3552281
Skewness1.972175647
Sum4.096827873 × 1015
Variance5.242571539 × 1017
MonotonicityNot monotonic
2024-12-30T17:03:30.794585image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1456118782 1
 
< 0.1%
1321585620 1
 
< 0.1%
2452323322 1
 
< 0.1%
1321585780 1
 
< 0.1%
1320143695 1
 
< 0.1%
2397792128 1
 
< 0.1%
1320143630 1
 
< 0.1%
1321585990 1
 
< 0.1%
1320143466 1
 
< 0.1%
1319132036 1
 
< 0.1%
Other values (2361455) 2361455
> 99.9%
ValueCountFrequency (%)
1317202451 1
< 0.1%
1317202452 1
< 0.1%
1317202459 1
< 0.1%
1317202464 1
< 0.1%
1317202465 1
< 0.1%
ValueCountFrequency (%)
4987328283 1
< 0.1%
4987328281 1
< 0.1%
4987328279 1
< 0.1%
4987328277 1
< 0.1%
4987328274 1
< 0.1%

accessRights
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

bibliographicCitation
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

language
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:30.882959image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters16530255
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 2361465
100.0%
2024-12-30T17:03:31.139151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 4722930
28.6%
0 4722930
28.6%
_ 4722930
28.6%
1 2361465
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16530255
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 4722930
28.6%
0 4722930
28.6%
_ 4722930
28.6%
1 2361465
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16530255
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 4722930
28.6%
0 4722930
28.6%
_ 4722930
28.6%
1 2361465
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16530255
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 4722930
28.6%
0 4722930
28.6%
_ 4722930
28.6%
1 2361465
14.3%
Distinct231346
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:31.269441image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters47229300
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103346 ?
Unique (%)4.4%

Sample

1st row2023-05-10T09:22:00Z
2nd row2022-01-03T14:31:00Z
3rd row2022-08-17T11:23:00Z
4th row2022-12-30T12:34:00Z
5th row2019-07-10T10:37:00Z
ValueCountFrequency (%)
2017-04-17t11:48:00z 2463
 
0.1%
2017-04-17t11:49:00z 2417
 
0.1%
2024-09-25t13:44:00z 2393
 
0.1%
2024-09-25t13:46:00z 2237
 
0.1%
2017-04-17t11:50:00z 2230
 
0.1%
2024-09-25t17:07:00z 2222
 
0.1%
2024-09-25t17:02:00z 2213
 
0.1%
2017-04-17t11:47:00z 2206
 
0.1%
2024-09-25t17:05:00z 2193
 
0.1%
2024-09-25t13:45:00z 2193
 
0.1%
Other values (231336) 2338698
99.0%
2024-12-30T17:03:31.459910image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11717287
24.8%
2 6603946
14.0%
1 5691138
12.1%
- 4722930
10.0%
: 4722930
10.0%
T 2361465
 
5.0%
Z 2361465
 
5.0%
4 1546512
 
3.3%
3 1539425
 
3.3%
5 1442680
 
3.1%
Other values (4) 4519522
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47229300
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 11717287
24.8%
2 6603946
14.0%
1 5691138
12.1%
- 4722930
10.0%
: 4722930
10.0%
T 2361465
 
5.0%
Z 2361465
 
5.0%
4 1546512
 
3.3%
3 1539425
 
3.3%
5 1442680
 
3.1%
Other values (4) 4519522
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47229300
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 11717287
24.8%
2 6603946
14.0%
1 5691138
12.1%
- 4722930
10.0%
: 4722930
10.0%
T 2361465
 
5.0%
Z 2361465
 
5.0%
4 1546512
 
3.3%
3 1539425
 
3.3%
5 1442680
 
3.1%
Other values (4) 4519522
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47229300
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 11717287
24.8%
2 6603946
14.0%
1 5691138
12.1%
- 4722930
10.0%
: 4722930
10.0%
T 2361465
 
5.0%
Z 2361465
 
5.0%
4 1546512
 
3.3%
3 1539425
 
3.3%
5 1442680
 
3.1%
Other values (4) 4519522
 
9.6%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:31.530422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters139326435
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 2361465
14.3%
museum 2361465
14.3%
of 2361465
14.3%
natural 2361465
14.3%
history 2361465
14.3%
smithsonian 2361465
14.3%
institution 2361465
14.3%
2024-12-30T17:03:31.639740image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 16530255
11.9%
i 14168790
10.2%
14168790
10.2%
o 11807325
 
8.5%
a 11807325
 
8.5%
n 11807325
 
8.5%
s 9445860
 
6.8%
u 9445860
 
6.8%
N 4722930
 
3.4%
m 4722930
 
3.4%
Other values (11) 30699045
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 139326435
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 16530255
11.9%
i 14168790
10.2%
14168790
10.2%
o 11807325
 
8.5%
a 11807325
 
8.5%
n 11807325
 
8.5%
s 9445860
 
6.8%
u 9445860
 
6.8%
N 4722930
 
3.4%
m 4722930
 
3.4%
Other values (11) 30699045
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 139326435
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 16530255
11.9%
i 14168790
10.2%
14168790
10.2%
o 11807325
 
8.5%
a 11807325
 
8.5%
n 11807325
 
8.5%
s 9445860
 
6.8%
u 9445860
 
6.8%
N 4722930
 
3.4%
m 4722930
 
3.4%
Other values (11) 30699045
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 139326435
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 16530255
11.9%
i 14168790
10.2%
14168790
10.2%
o 11807325
 
8.5%
a 11807325
 
8.5%
n 11807325
 
8.5%
s 9445860
 
6.8%
u 9445860
 
6.8%
N 4722930
 
3.4%
m 4722930
 
3.4%
Other values (11) 30699045
22.0%

references
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

rightsHolder
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

type
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB
Distinct37
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:31.715778image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length28.98757847
Min length2

Characters and Unicode

Total characters68453152
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:15463
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 1210996
51.3%
urn:lsid:biocol.org:col:15463 1149313
48.7%
nsmt 255
 
< 0.1%
uam 205
 
< 0.1%
rmnh 94
 
< 0.1%
nrm 92
 
< 0.1%
nmv 65
 
< 0.1%
rcs 61
 
< 0.1%
zmmu 46
 
< 0.1%
nmsz 44
 
< 0.1%
Other values (27) 294
 
< 0.1%
2024-12-30T17:03:31.852163image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 9441236
13.8%
o 9441236
13.8%
l 7080927
 
10.3%
i 4720618
 
6.9%
c 4720618
 
6.9%
r 4720618
 
6.9%
n 2360309
 
3.4%
u 2360309
 
3.4%
d 2360309
 
3.4%
s 2360309
 
3.4%
Other values (30) 18886663
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 68453152
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
: 9441236
13.8%
o 9441236
13.8%
l 7080927
 
10.3%
i 4720618
 
6.9%
c 4720618
 
6.9%
r 4720618
 
6.9%
n 2360309
 
3.4%
u 2360309
 
3.4%
d 2360309
 
3.4%
s 2360309
 
3.4%
Other values (30) 18886663
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 68453152
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
: 9441236
13.8%
o 9441236
13.8%
l 7080927
 
10.3%
i 4720618
 
6.9%
c 4720618
 
6.9%
r 4720618
 
6.9%
n 2360309
 
3.4%
u 2360309
 
3.4%
d 2360309
 
3.4%
s 2360309
 
3.4%
Other values (30) 18886663
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 68453152
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
: 9441236
13.8%
o 9441236
13.8%
l 7080927
 
10.3%
i 4720618
 
6.9%
c 4720618
 
6.9%
r 4720618
 
6.9%
n 2360309
 
3.4%
u 2360309
 
3.4%
d 2360309
 
3.4%
s 2360309
 
3.4%
Other values (30) 18886663
27.6%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:31.931674image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters106265925
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
2nd rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
3rd rowurn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0
4th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
5th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
ValueCountFrequency (%)
urn:uuid:60e28f81-e634-4869-aa3e-732caed713c8 1149313
48.7%
urn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6 490281
20.8%
urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad 154106
 
6.5%
urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22 152955
 
6.5%
urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893 149231
 
6.3%
urn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0 148897
 
6.3%
urn:uuid:09c9cf5f-f5d3-48cc-b5c8-cd9b9fbd631f 116682
 
4.9%
2024-12-30T17:03:32.059781image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9445860
 
8.9%
8 8119933
 
7.6%
d 7177833
 
6.8%
u 7084395
 
6.7%
3 6484963
 
6.1%
e 5998632
 
5.6%
c 5829987
 
5.5%
1 5730164
 
5.4%
a 5303855
 
5.0%
6 5120107
 
4.8%
Other values (12) 39970196
37.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 106265925
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 9445860
 
8.9%
8 8119933
 
7.6%
d 7177833
 
6.8%
u 7084395
 
6.7%
3 6484963
 
6.1%
e 5998632
 
5.6%
c 5829987
 
5.5%
1 5730164
 
5.4%
a 5303855
 
5.0%
6 5120107
 
4.8%
Other values (12) 39970196
37.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 106265925
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 9445860
 
8.9%
8 8119933
 
7.6%
d 7177833
 
6.8%
u 7084395
 
6.7%
3 6484963
 
6.1%
e 5998632
 
5.6%
c 5829987
 
5.5%
1 5730164
 
5.4%
a 5303855
 
5.0%
6 5120107
 
4.8%
Other values (12) 39970196
37.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 106265925
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 9445860
 
8.9%
8 8119933
 
7.6%
d 7177833
 
6.8%
u 7084395
 
6.7%
3 6484963
 
6.1%
e 5998632
 
5.6%
c 5829987
 
5.5%
1 5730164
 
5.4%
a 5303855
 
5.0%
6 5120107
 
4.8%
Other values (12) 39970196
37.6%

datasetID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB
Distinct37
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:32.125635image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.026426816
Min length2

Characters and Unicode

Total characters7146801
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowUSNM
2nd rowUS
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 1210996
51.3%
us 1149313
48.7%
nsmt 255
 
< 0.1%
uam 205
 
< 0.1%
rmnh 94
 
< 0.1%
nrm 92
 
< 0.1%
nmv 65
 
< 0.1%
rcs 61
 
< 0.1%
zmmu 46
 
< 0.1%
nmsz 44
 
< 0.1%
Other values (27) 294
 
< 0.1%
2024-12-30T17:03:32.253939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 2360768
33.0%
U 2360615
33.0%
M 1212124
17.0%
N 1211677
17.0%
A 347
 
< 0.1%
T 255
 
< 0.1%
R 251
 
< 0.1%
H 151
 
< 0.1%
C 125
 
< 0.1%
Z 116
 
< 0.1%
Other values (10) 372
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7146801
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 2360768
33.0%
U 2360615
33.0%
M 1212124
17.0%
N 1211677
17.0%
A 347
 
< 0.1%
T 255
 
< 0.1%
R 251
 
< 0.1%
H 151
 
< 0.1%
C 125
 
< 0.1%
Z 116
 
< 0.1%
Other values (10) 372
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7146801
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 2360768
33.0%
U 2360615
33.0%
M 1212124
17.0%
N 1211677
17.0%
A 347
 
< 0.1%
T 255
 
< 0.1%
R 251
 
< 0.1%
H 151
 
< 0.1%
C 125
 
< 0.1%
Z 116
 
< 0.1%
Other values (10) 372
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7146801
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 2360768
33.0%
U 2360615
33.0%
M 1212124
17.0%
N 1211677
17.0%
A 347
 
< 0.1%
T 255
 
< 0.1%
R 251
 
< 0.1%
H 151
 
< 0.1%
C 125
 
< 0.1%
Z 116
 
< 0.1%
Other values (10) 372
 
< 0.1%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:32.301939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.609311169
Min length2

Characters and Unicode

Total characters6161797
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIZ
2nd rowUS
3rd rowHERP
4th rowIZ
5th rowIZ
ValueCountFrequency (%)
us 1149313
48.7%
iz 490281
20.8%
ent 154106
 
6.5%
mamm 152955
 
6.5%
birds 149231
 
6.3%
herp 148897
 
6.3%
fish 116682
 
4.9%
2024-12-30T17:03:32.404325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1415226
23.0%
U 1149313
18.7%
I 756194
12.3%
Z 490281
 
8.0%
M 458865
 
7.4%
E 303003
 
4.9%
R 298128
 
4.8%
H 265579
 
4.3%
N 154106
 
2.5%
T 154106
 
2.5%
Other values (5) 716996
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6161797
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1415226
23.0%
U 1149313
18.7%
I 756194
12.3%
Z 490281
 
8.0%
M 458865
 
7.4%
E 303003
 
4.9%
R 298128
 
4.8%
H 265579
 
4.3%
N 154106
 
2.5%
T 154106
 
2.5%
Other values (5) 716996
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6161797
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1415226
23.0%
U 1149313
18.7%
I 756194
12.3%
Z 490281
 
8.0%
M 458865
 
7.4%
E 303003
 
4.9%
R 298128
 
4.8%
H 265579
 
4.3%
N 154106
 
2.5%
T 154106
 
2.5%
Other values (5) 716996
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6161797
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1415226
23.0%
U 1149313
18.7%
I 756194
12.3%
Z 490281
 
8.0%
M 458865
 
7.4%
E 303003
 
4.9%
R 298128
 
4.8%
H 265579
 
4.3%
N 154106
 
2.5%
T 154106
 
2.5%
Other values (5) 716996
11.6%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:32.463379image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters44867835
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 2361465
33.3%
extant 2361465
33.3%
biology 2361465
33.3%
2024-12-30T17:03:32.570440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 4722930
 
10.5%
t 4722930
 
10.5%
4722930
 
10.5%
o 4722930
 
10.5%
H 2361465
 
5.3%
E 2361465
 
5.3%
M 2361465
 
5.3%
x 2361465
 
5.3%
a 2361465
 
5.3%
B 2361465
 
5.3%
Other values (5) 11807325
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 44867835
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 4722930
 
10.5%
t 4722930
 
10.5%
4722930
 
10.5%
o 4722930
 
10.5%
H 2361465
 
5.3%
E 2361465
 
5.3%
M 2361465
 
5.3%
x 2361465
 
5.3%
a 2361465
 
5.3%
B 2361465
 
5.3%
Other values (5) 11807325
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 44867835
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 4722930
 
10.5%
t 4722930
 
10.5%
4722930
 
10.5%
o 4722930
 
10.5%
H 2361465
 
5.3%
E 2361465
 
5.3%
M 2361465
 
5.3%
x 2361465
 
5.3%
a 2361465
 
5.3%
B 2361465
 
5.3%
Other values (5) 11807325
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 44867835
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 4722930
 
10.5%
t 4722930
 
10.5%
4722930
 
10.5%
o 4722930
 
10.5%
H 2361465
 
5.3%
E 2361465
 
5.3%
M 2361465
 
5.3%
x 2361465
 
5.3%
a 2361465
 
5.3%
B 2361465
 
5.3%
Other values (5) 11807325
26.3%

ownerInstitutionCode
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:32.630604image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length18
Mean length18.00610511
Min length17

Characters and Unicode

Total characters42520787
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESERVED_SPECIMEN
2nd rowPRESERVED_SPECIMEN
3rd rowPRESERVED_SPECIMEN
4th rowPRESERVED_SPECIMEN
5th rowPRESERVED_SPECIMEN
ValueCountFrequency (%)
preserved_specimen 2329870
98.7%
machine_observation 23006
 
1.0%
human_observation 8589
 
0.4%
2024-12-30T17:03:32.758102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 11703951
27.5%
S 4691335
11.0%
R 4691335
11.0%
P 4659740
 
11.0%
N 2393060
 
5.6%
I 2384471
 
5.6%
V 2361465
 
5.6%
M 2361465
 
5.6%
_ 2361465
 
5.6%
C 2352876
 
5.5%
Other values (7) 2559624
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42520787
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 11703951
27.5%
S 4691335
11.0%
R 4691335
11.0%
P 4659740
 
11.0%
N 2393060
 
5.6%
I 2384471
 
5.6%
V 2361465
 
5.6%
M 2361465
 
5.6%
_ 2361465
 
5.6%
C 2352876
 
5.5%
Other values (7) 2559624
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42520787
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 11703951
27.5%
S 4691335
11.0%
R 4691335
11.0%
P 4659740
 
11.0%
N 2393060
 
5.6%
I 2384471
 
5.6%
V 2361465
 
5.6%
M 2361465
 
5.6%
_ 2361465
 
5.6%
C 2352876
 
5.5%
Other values (7) 2559624
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42520787
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 11703951
27.5%
S 4691335
11.0%
R 4691335
11.0%
P 4659740
 
11.0%
N 2393060
 
5.6%
I 2384471
 
5.6%
V 2361465
 
5.6%
M 2361465
 
5.6%
_ 2361465
 
5.6%
C 2352876
 
5.5%
Other values (7) 2559624
 
6.0%

informationWithheld
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

dataGeneralizations
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

dynamicProperties
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

occurrenceID
Text

Unique 

Distinct2361465
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:33.713072image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length62.99999068
Min length41

Characters and Unicode

Total characters148772273
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2361465 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3c1d5cd1b-23f9-4aab-8cd8-011e6535be18
2nd rowhttp://n2t.net/ark:/65665/38212d138-cfcd-4363-8d3b-93b82afc1d4b
3rd rowhttp://n2t.net/ark:/65665/3c1d69371-acc7-4c47-bc57-9d5ba7994267
4th rowhttp://n2t.net/ark:/65665/382140f93-30c1-4f26-bd0c-77d197d5ebc0
5th rowhttp://n2t.net/ark:/65665/3c1d814f8-bb57-4c37-a953-dd84b1c6415d
ValueCountFrequency (%)
http://n2t.net/ark:/65665/382180c8b-f0ba-4b41-aeb2-e2c12d24092c 1
 
< 0.1%
http://n2t.net/ark:/65665/355628743-eda7 1
 
< 0.1%
http://n2t.net/ark:/65665/3c1d5cd1b-23f9-4aab-8cd8-011e6535be18 1
 
< 0.1%
http://n2t.net/ark:/65665/38212d138-cfcd-4363-8d3b-93b82afc1d4b 1
 
< 0.1%
http://n2t.net/ark:/65665/3c1d69371-acc7-4c47-bc57-9d5ba7994267 1
 
< 0.1%
http://n2t.net/ark:/65665/382140f93-30c1-4f26-bd0c-77d197d5ebc0 1
 
< 0.1%
http://n2t.net/ark:/65665/3c1d814f8-bb57-4c37-a953-dd84b1c6415d 1
 
< 0.1%
http://n2t.net/ark:/65665/38215186e-af4f-46dc-8b81-ec58617bdfd7 1
 
< 0.1%
http://n2t.net/ark:/65665/3c1d9c4a8-7ba7-48dd-b92e-9924960b16d2 1
 
< 0.1%
http://n2t.net/ark:/65665/3962cadac-16d6-4f21-8ca2-8289c40780c6 1
 
< 0.1%
Other values (2361455) 2361455
> 99.9%
2024-12-30T17:03:34.699115image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 11807325
 
7.9%
6 11516224
 
7.7%
t 9445860
 
6.3%
- 9445858
 
6.3%
5 9149775
 
6.2%
a 7384434
 
5.0%
2 6789545
 
4.6%
3 6788543
 
4.6%
4 6786951
 
4.6%
e 6782964
 
4.6%
Other values (16) 62874794
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 148772273
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 11807325
 
7.9%
6 11516224
 
7.7%
t 9445860
 
6.3%
- 9445858
 
6.3%
5 9149775
 
6.2%
a 7384434
 
5.0%
2 6789545
 
4.6%
3 6788543
 
4.6%
4 6786951
 
4.6%
e 6782964
 
4.6%
Other values (16) 62874794
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 148772273
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 11807325
 
7.9%
6 11516224
 
7.7%
t 9445860
 
6.3%
- 9445858
 
6.3%
5 9149775
 
6.2%
a 7384434
 
5.0%
2 6789545
 
4.6%
3 6788543
 
4.6%
4 6786951
 
4.6%
e 6782964
 
4.6%
Other values (16) 62874794
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 148772273
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 11807325
 
7.9%
6 11516224
 
7.7%
t 9445860
 
6.3%
- 9445858
 
6.3%
5 9149775
 
6.2%
a 7384434
 
5.0%
2 6789545
 
4.6%
3 6788543
 
4.6%
4 6786951
 
4.6%
e 6782964
 
4.6%
Other values (16) 62874794
42.3%

catalogNumber
Text

Missing 

Distinct1790642
Distinct (%)83.4%
Missing213211
Missing (%)9.0%
Memory size18.0 MiB
2024-12-30T17:03:35.500593image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length21
Mean length10.54068094
Min length4

Characters and Unicode

Total characters22644060
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1533815 ?
Unique (%)71.4%

Sample

1st rowUSNM 1220020
2nd rowUS 2327562
3rd rowUSNM 359728
4th rowUSNM 65866
5th rowUSNM 1569732
ValueCountFrequency (%)
usnm 1056889
25.2%
us 984432
23.5%
herp 1447
 
< 0.1%
tissue 1416
 
< 0.1%
sem 65
 
< 0.1%
48
 
< 0.1%
1 41
 
< 0.1%
stub 40
 
< 0.1%
image 31
 
< 0.1%
micrograph 25
 
< 0.1%
Other values (1602731) 2148320
51.2%
2024-12-30T17:03:36.390195image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 2152369
 
9.5%
U 2147420
 
9.5%
2044500
 
9.0%
1 1805408
 
8.0%
2 1634072
 
7.2%
3 1537032
 
6.8%
0 1310814
 
5.8%
4 1307098
 
5.8%
5 1283378
 
5.7%
N 1249864
 
5.5%
Other values (57) 6172105
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22644060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 2152369
 
9.5%
U 2147420
 
9.5%
2044500
 
9.0%
1 1805408
 
8.0%
2 1634072
 
7.2%
3 1537032
 
6.8%
0 1310814
 
5.8%
4 1307098
 
5.8%
5 1283378
 
5.7%
N 1249864
 
5.5%
Other values (57) 6172105
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22644060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 2152369
 
9.5%
U 2147420
 
9.5%
2044500
 
9.0%
1 1805408
 
8.0%
2 1634072
 
7.2%
3 1537032
 
6.8%
0 1310814
 
5.8%
4 1307098
 
5.8%
5 1283378
 
5.7%
N 1249864
 
5.5%
Other values (57) 6172105
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22644060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 2152369
 
9.5%
U 2147420
 
9.5%
2044500
 
9.0%
1 1805408
 
8.0%
2 1634072
 
7.2%
3 1537032
 
6.8%
0 1310814
 
5.8%
4 1307098
 
5.8%
5 1283378
 
5.7%
N 1249864
 
5.5%
Other values (57) 6172105
27.3%

recordNumber
Text

Missing 

Distinct253148
Distinct (%)19.2%
Missing1045436
Missing (%)44.3%
Memory size18.0 MiB
2024-12-30T17:03:36.608279image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length93
Median length90
Mean length4.785215979
Min length1

Characters and Unicode

Total characters6297483
Distinct characters104
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197321 ?
Unique (%)15.0%

Sample

1st row5209
2nd rowUSNPC # 008843
3rd rowUSNPC # 074963
4th row478
5th rows.n.
ValueCountFrequency (%)
s.n 164137
 
11.2%
26102
 
1.8%
usnpc 22710
 
1.5%
no 12214
 
0.8%
number 11997
 
0.8%
bureau 5232
 
0.4%
eyd 4047
 
0.3%
s 3600
 
0.2%
of 3507
 
0.2%
n 3489
 
0.2%
Other values (191948) 1214292
82.5%
2024-12-30T17:03:36.883767image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 716219
11.4%
2 556075
 
8.8%
3 479210
 
7.6%
0 459757
 
7.3%
4 448402
 
7.1%
5 430655
 
6.8%
6 416988
 
6.6%
7 393872
 
6.3%
8 377940
 
6.0%
9 367751
 
5.8%
Other values (94) 1650614
26.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6297483
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 716219
11.4%
2 556075
 
8.8%
3 479210
 
7.6%
0 459757
 
7.3%
4 448402
 
7.1%
5 430655
 
6.8%
6 416988
 
6.6%
7 393872
 
6.3%
8 377940
 
6.0%
9 367751
 
5.8%
Other values (94) 1650614
26.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6297483
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 716219
11.4%
2 556075
 
8.8%
3 479210
 
7.6%
0 459757
 
7.3%
4 448402
 
7.1%
5 430655
 
6.8%
6 416988
 
6.6%
7 393872
 
6.3%
8 377940
 
6.0%
9 367751
 
5.8%
Other values (94) 1650614
26.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6297483
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 716219
11.4%
2 556075
 
8.8%
3 479210
 
7.6%
0 459757
 
7.3%
4 448402
 
7.1%
5 430655
 
6.8%
6 416988
 
6.6%
7 393872
 
6.3%
8 377940
 
6.0%
9 367751
 
5.8%
Other values (94) 1650614
26.2%

recordedBy
Text

Missing 

Distinct115852
Distinct (%)6.2%
Missing498671
Missing (%)21.1%
Memory size18.0 MiB
2024-12-30T17:03:37.030073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length239
Median length171
Mean length17.19955669
Min length1

Characters and Unicode

Total characters32039231
Distinct characters143
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56990 ?
Unique (%)3.1%

Sample

1st rowG. Hendler
2nd rowR. C. Rollins & D. Rollins
3rd rowT. Vaughan
4th rowD. Harper
5th rowF. Harvey
ValueCountFrequency (%)
413360
 
6.3%
j 303892
 
4.6%
a 242830
 
3.7%
r 228708
 
3.5%
e 216487
 
3.3%
c 207627
 
3.2%
m 197349
 
3.0%
h 179142
 
2.7%
w 156602
 
2.4%
l 143932
 
2.2%
Other values (44536) 4249852
65.0%
2024-12-30T17:03:37.238394image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4676987
 
14.6%
. 2978676
 
9.3%
e 2217317
 
6.9%
a 1603554
 
5.0%
r 1548203
 
4.8%
n 1462457
 
4.6%
o 1456025
 
4.5%
i 1334926
 
4.2%
l 1157607
 
3.6%
t 1153389
 
3.6%
Other values (133) 12450090
38.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32039231
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4676987
 
14.6%
. 2978676
 
9.3%
e 2217317
 
6.9%
a 1603554
 
5.0%
r 1548203
 
4.8%
n 1462457
 
4.6%
o 1456025
 
4.5%
i 1334926
 
4.2%
l 1157607
 
3.6%
t 1153389
 
3.6%
Other values (133) 12450090
38.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32039231
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4676987
 
14.6%
. 2978676
 
9.3%
e 2217317
 
6.9%
a 1603554
 
5.0%
r 1548203
 
4.8%
n 1462457
 
4.6%
o 1456025
 
4.5%
i 1334926
 
4.2%
l 1157607
 
3.6%
t 1153389
 
3.6%
Other values (133) 12450090
38.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32039231
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4676987
 
14.6%
. 2978676
 
9.3%
e 2217317
 
6.9%
a 1603554
 
5.0%
r 1548203
 
4.8%
n 1462457
 
4.6%
o 1456025
 
4.5%
i 1334926
 
4.2%
l 1157607
 
3.6%
t 1153389
 
3.6%
Other values (133) 12450090
38.9%

recordedByID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

individualCount
Real number (ℝ)

Skewed 

Distinct819
Distinct (%)< 0.1%
Missing1023
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.646172624
Minimum0
Maximum30622
Zeros3253
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:37.299065image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum30622
Range30622
Interquartile range (IQR)0

Descriptive statistics

Standard deviation44.63296734
Coefficient of variation (CV)16.86699006
Kurtosis194754.4753
Mean2.646172624
Median Absolute Deviation (MAD)0
Skewness350.7736071
Sum6246137
Variance1992.101773
MonotonicityNot monotonic
2024-12-30T17:03:37.355552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2047193
86.7%
2 94184
 
4.0%
3 46374
 
2.0%
4 33192
 
1.4%
5 24016
 
1.0%
6 16667
 
0.7%
10 12127
 
0.5%
7 10535
 
0.4%
8 9696
 
0.4%
9 6408
 
0.3%
Other values (809) 60050
 
2.5%
ValueCountFrequency (%)
0 3253
 
0.1%
1 2047193
86.7%
2 94184
 
4.0%
3 46374
 
2.0%
4 33192
 
1.4%
ValueCountFrequency (%)
30622 1
< 0.1%
28708 1
< 0.1%
19139 1
< 0.1%
15284 1
< 0.1%
10526 1
< 0.1%

organismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

organismQuantityType
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

sex
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing2009605
Missing (%)85.1%
Memory size18.0 MiB
2024-12-30T17:03:37.409553image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.899238333
Min length4

Characters and Unicode

Total characters1723846
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFEMALE
2nd rowMALE
3rd rowMALE
4th rowMALE
5th rowMALE
ValueCountFrequency (%)
male 193937
55.1%
female 157843
44.9%
hermaphrodite 80
 
< 0.1%
2024-12-30T17:03:37.512435image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 509783
29.6%
M 351860
20.4%
A 351860
20.4%
L 351780
20.4%
F 157843
 
9.2%
H 160
 
< 0.1%
R 160
 
< 0.1%
P 80
 
< 0.1%
O 80
 
< 0.1%
D 80
 
< 0.1%
Other values (2) 160
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1723846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 509783
29.6%
M 351860
20.4%
A 351860
20.4%
L 351780
20.4%
F 157843
 
9.2%
H 160
 
< 0.1%
R 160
 
< 0.1%
P 80
 
< 0.1%
O 80
 
< 0.1%
D 80
 
< 0.1%
Other values (2) 160
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1723846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 509783
29.6%
M 351860
20.4%
A 351860
20.4%
L 351780
20.4%
F 157843
 
9.2%
H 160
 
< 0.1%
R 160
 
< 0.1%
P 80
 
< 0.1%
O 80
 
< 0.1%
D 80
 
< 0.1%
Other values (2) 160
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1723846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 509783
29.6%
M 351860
20.4%
A 351860
20.4%
L 351780
20.4%
F 157843
 
9.2%
H 160
 
< 0.1%
R 160
 
< 0.1%
P 80
 
< 0.1%
O 80
 
< 0.1%
D 80
 
< 0.1%
Other values (2) 160
 
< 0.1%

lifeStage
Text

Missing 

Distinct30
Distinct (%)< 0.1%
Missing2107141
Missing (%)89.2%
Memory size18.0 MiB
2024-12-30T17:03:37.570976image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.528035105
Min length3

Characters and Unicode

Total characters1660236
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowAdult
4th rowFruiting
5th rowFlowering
ValueCountFrequency (%)
adult 137713
54.1%
flowering 49923
 
19.6%
fruiting 26364
 
10.4%
juvenile 15425
 
6.1%
immature 8914
 
3.5%
vegetative 6008
 
2.4%
larva 5218
 
2.1%
subadult 1137
 
0.4%
chick 960
 
0.4%
embryo 589
 
0.2%
Other values (20) 2073
 
0.8%
2024-12-30T17:03:37.689383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 204967
12.3%
u 191206
11.5%
t 187476
11.3%
d 138858
8.4%
A 137713
8.3%
i 125782
7.6%
e 108742
 
6.5%
n 93053
 
5.6%
r 91120
 
5.5%
g 83572
 
5.0%
Other values (29) 297747
17.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1660236
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 204967
12.3%
u 191206
11.5%
t 187476
11.3%
d 138858
8.4%
A 137713
8.3%
i 125782
7.6%
e 108742
 
6.5%
n 93053
 
5.6%
r 91120
 
5.5%
g 83572
 
5.0%
Other values (29) 297747
17.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1660236
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 204967
12.3%
u 191206
11.5%
t 187476
11.3%
d 138858
8.4%
A 137713
8.3%
i 125782
7.6%
e 108742
 
6.5%
n 93053
 
5.6%
r 91120
 
5.5%
g 83572
 
5.0%
Other values (29) 297747
17.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1660236
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 204967
12.3%
u 191206
11.5%
t 187476
11.3%
d 138858
8.4%
A 137713
8.3%
i 125782
7.6%
e 108742
 
6.5%
n 93053
 
5.6%
r 91120
 
5.5%
g 83572
 
5.0%
Other values (29) 297747
17.9%

reproductiveCondition
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

caste
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

behavior
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

vitality
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

establishmentMeans
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

degreeOfEstablishment
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

pathway
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

georeferenceVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB
Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:37.739917image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.999555784
Min length6

Characters and Unicode

Total characters16529199
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 2360415
> 99.9%
absent 1049
 
< 0.1%
2024-12-30T17:03:37.840182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 4721879
28.6%
S 2361464
14.3%
T 2361464
14.3%
N 2361464
14.3%
P 2360415
14.3%
R 2360415
14.3%
A 1049
 
< 0.1%
B 1049
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16529199
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 4721879
28.6%
S 2361464
14.3%
T 2361464
14.3%
N 2361464
14.3%
P 2360415
14.3%
R 2360415
14.3%
A 1049
 
< 0.1%
B 1049
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16529199
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 4721879
28.6%
S 2361464
14.3%
T 2361464
14.3%
N 2361464
14.3%
P 2360415
14.3%
R 2360415
14.3%
A 1049
 
< 0.1%
B 1049
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16529199
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 4721879
28.6%
S 2361464
14.3%
T 2361464
14.3%
N 2361464
14.3%
P 2360415
14.3%
R 2360415
14.3%
A 1049
 
< 0.1%
B 1049
 
< 0.1%

preparations
Text

Missing 

Distinct1125
Distinct (%)0.1%
Missing1223403
Missing (%)51.8%
Memory size18.0 MiB
2024-12-30T17:03:37.993808image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length192
Median length154
Mean length9.646144059
Min length3

Characters and Unicode

Total characters10977910
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique452 ?
Unique (%)< 0.1%

Sample

1st rowAlcohol (Ethanol)
2nd rowEthanol
3rd rowDry
4th rowAlcohol (Ethanol)
5th rowPinned
ValueCountFrequency (%)
ethanol 373474
21.8%
dry 234832
13.7%
alcohol 228646
13.3%
skin 213511
12.5%
whole 136729
 
8.0%
skull 114952
 
6.7%
pinned 99258
 
5.8%
slide 49717
 
2.9%
fluid 34184
 
2.0%
envelope 29335
 
1.7%
Other values (239) 199694
11.6%
2024-12-30T17:03:38.229866image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1411526
 
12.9%
o 1133311
 
10.3%
n 892184
 
8.1%
h 772056
 
7.0%
576270
 
5.2%
i 492138
 
4.5%
e 477120
 
4.3%
a 473891
 
4.3%
t 460110
 
4.2%
S 424072
 
3.9%
Other values (64) 3865232
35.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10977910
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1411526
 
12.9%
o 1133311
 
10.3%
n 892184
 
8.1%
h 772056
 
7.0%
576270
 
5.2%
i 492138
 
4.5%
e 477120
 
4.3%
a 473891
 
4.3%
t 460110
 
4.2%
S 424072
 
3.9%
Other values (64) 3865232
35.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10977910
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1411526
 
12.9%
o 1133311
 
10.3%
n 892184
 
8.1%
h 772056
 
7.0%
576270
 
5.2%
i 492138
 
4.5%
e 477120
 
4.3%
a 473891
 
4.3%
t 460110
 
4.2%
S 424072
 
3.9%
Other values (64) 3865232
35.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10977910
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1411526
 
12.9%
o 1133311
 
10.3%
n 892184
 
8.1%
h 772056
 
7.0%
576270
 
5.2%
i 492138
 
4.5%
e 477120
 
4.3%
a 473891
 
4.3%
t 460110
 
4.2%
S 424072
 
3.9%
Other values (64) 3865232
35.2%

disposition
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

associatedOccurrences
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

associatedReferences
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

associatedSequences
Text

Missing 

Distinct3083
Distinct (%)99.4%
Missing2358364
Missing (%)99.9%
Memory size18.0 MiB
2024-12-30T17:03:38.318210image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12558
Median length49
Mean length106.4991938
Min length47

Characters and Unicode

Total characters330254
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3075 ?
Unique (%)99.2%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KM080038
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=EU823242;https://www.ncbi.nlm.nih.gov/gquery?term=EU823167;https://www.ncbi.nlm.nih.gov/gquery?term=KC246618
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MN549733
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KC771789;https://www.ncbi.nlm.nih.gov/gquery?term=KC771632
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=HQ600894
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=prjna521985 8
 
0.3%
https://www.ncbi.nlm.nih.gov/gquery?term=km521547 5
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273864 3
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273835 2
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=kf989555;https://www.ncbi.nlm.nih.gov/gquery?term=kf989872;https://www.ncbi.nlm.nih.gov/gquery?term=kf989774;https://www.ncbi.nlm.nih.gov/gquery?term=kf989974;https://www.ncbi.nlm.nih.gov/gquery?term=kf989663 2
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mh244118 2
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837192;https://www.ncbi.nlm.nih.gov/gquery?term=jn837282;https://www.ncbi.nlm.nih.gov/gquery?term=jn837372;https://www.ncbi.nlm.nih.gov/gquery?term=jn837475 2
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=kp739770 2
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=hq543050 1
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mk246578;https://www.ncbi.nlm.nih.gov/gquery?term=mk246482;https://www.ncbi.nlm.nih.gov/gquery?term=mk246483 1
 
< 0.1%
Other values (3073) 3073
99.1%
2024-12-30T17:03:38.468094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 26569
 
8.0%
/ 19917
 
6.0%
t 19917
 
6.0%
n 19917
 
6.0%
w 19917
 
6.0%
h 13278
 
4.0%
m 13278
 
4.0%
g 13278
 
4.0%
i 13278
 
4.0%
e 13278
 
4.0%
Other values (53) 157627
47.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 330254
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 26569
 
8.0%
/ 19917
 
6.0%
t 19917
 
6.0%
n 19917
 
6.0%
w 19917
 
6.0%
h 13278
 
4.0%
m 13278
 
4.0%
g 13278
 
4.0%
i 13278
 
4.0%
e 13278
 
4.0%
Other values (53) 157627
47.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 330254
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 26569
 
8.0%
/ 19917
 
6.0%
t 19917
 
6.0%
n 19917
 
6.0%
w 19917
 
6.0%
h 13278
 
4.0%
m 13278
 
4.0%
g 13278
 
4.0%
i 13278
 
4.0%
e 13278
 
4.0%
Other values (53) 157627
47.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 330254
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 26569
 
8.0%
/ 19917
 
6.0%
t 19917
 
6.0%
n 19917
 
6.0%
w 19917
 
6.0%
h 13278
 
4.0%
m 13278
 
4.0%
g 13278
 
4.0%
i 13278
 
4.0%
e 13278
 
4.0%
Other values (53) 157627
47.7%

associatedTaxa
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

otherCatalogNumbers
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

occurrenceRemarks
Text

Missing 

Distinct167090
Distinct (%)53.2%
Missing2047567
Missing (%)86.7%
Memory size18.0 MiB
2024-12-30T17:03:38.647495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length197627
Median length2471
Mean length67.06642285
Min length1

Characters and Unicode

Total characters21052016
Distinct characters164
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146194 ?
Unique (%)46.6%

Sample

1st rowNinoe sp. B
2nd row{"hostGen":"Wallago","hostSpec":"after","hostBodyLoc":"stomach"}; Original USNPC preservative was a solution of 70% ethanol, 3% formalin, and 2% glycerine
3rd row{"hostGen":"Catoptrophorus","hostSpec":"semipalmatus","hostBodyLoc":"esophagus","hostFldNo":"JEBadley-426-23"}; Glycerin jelly
4th rowScripps Institution of Oceanography library archives about M.J. Johnson Phyllosoma Collection: specimens were stained with fast green and are mounted mostly in Canada balsam, Harleco synthetic resin or diatex.
5th row8/28/28; 6527; Orcutt; Chamberlain Coll
ValueCountFrequency (%)
of 64175
 
2.1%
by 48563
 
1.6%
and 45625
 
1.5%
the 43984
 
1.4%
coll 38399
 
1.3%
34598
 
1.1%
a 34536
 
1.1%
to 31161
 
1.0%
was 27075
 
0.9%
in 26226
 
0.9%
Other values (150527) 2642348
87.0%
2024-12-30T17:03:38.902516image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2687785
 
12.8%
e 1443718
 
6.9%
o 1130054
 
5.4%
a 1127958
 
5.4%
i 1022015
 
4.9%
t 975032
 
4.6%
n 951381
 
4.5%
r 864148
 
4.1%
s 821033
 
3.9%
l 811712
 
3.9%
Other values (154) 9217180
43.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21052016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2687785
 
12.8%
e 1443718
 
6.9%
o 1130054
 
5.4%
a 1127958
 
5.4%
i 1022015
 
4.9%
t 975032
 
4.6%
n 951381
 
4.5%
r 864148
 
4.1%
s 821033
 
3.9%
l 811712
 
3.9%
Other values (154) 9217180
43.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21052016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2687785
 
12.8%
e 1443718
 
6.9%
o 1130054
 
5.4%
a 1127958
 
5.4%
i 1022015
 
4.9%
t 975032
 
4.6%
n 951381
 
4.5%
r 864148
 
4.1%
s 821033
 
3.9%
l 811712
 
3.9%
Other values (154) 9217180
43.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21052016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2687785
 
12.8%
e 1443718
 
6.9%
o 1130054
 
5.4%
a 1127958
 
5.4%
i 1022015
 
4.9%
t 975032
 
4.6%
n 951381
 
4.5%
r 864148
 
4.1%
s 821033
 
3.9%
l 811712
 
3.9%
Other values (154) 9217180
43.8%

organismID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

organismName
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

organismScope
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

associatedOrganisms
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

previousIdentifications
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

organismRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

materialEntityID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

materialEntityRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

verbatimLabel
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB

materialSampleID
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB

eventID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

parentEventID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

eventType
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:38.960148image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowBaffin Island
ValueCountFrequency (%)
baffin 1
50.0%
island 1
50.0%
2024-12-30T17:03:39.062391image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
15.4%
f 2
15.4%
n 2
15.4%
B 1
7.7%
i 1
7.7%
1
7.7%
I 1
7.7%
s 1
7.7%
l 1
7.7%
d 1
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
15.4%
f 2
15.4%
n 2
15.4%
B 1
7.7%
i 1
7.7%
1
7.7%
I 1
7.7%
s 1
7.7%
l 1
7.7%
d 1
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
15.4%
f 2
15.4%
n 2
15.4%
B 1
7.7%
i 1
7.7%
1
7.7%
I 1
7.7%
s 1
7.7%
l 1
7.7%
d 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
15.4%
f 2
15.4%
n 2
15.4%
B 1
7.7%
i 1
7.7%
1
7.7%
I 1
7.7%
s 1
7.7%
l 1
7.7%
d 1
7.7%

fieldNumber
Text

Missing 

Distinct48666
Distinct (%)24.7%
Missing2164707
Missing (%)91.7%
Memory size18.0 MiB
2024-12-30T17:03:39.204611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length97
Median length64
Mean length12.74822879
Min length1

Characters and Unicode

Total characters2508316
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22801 ?
Unique (%)11.6%

Sample

1st rowMMS-MAMES/B3:M4-4
2nd rowUSARP/EL/9/740/USC
3rd rowM165503; H.29-118
4th rowUSFC/A5151
5th rowUSARP/EL/6/369/USC
ValueCountFrequency (%)
vgs 4890
 
1.9%
mms-mafla/jar 4303
 
1.7%
jtw 3701
 
1.4%
bolland/rfb 1880
 
0.7%
bbc 1566
 
0.6%
humes 1397
 
0.5%
1387
 
0.5%
jpem 1304
 
0.5%
lwk 1042
 
0.4%
lk 1037
 
0.4%
Other values (46561) 233531
91.2%
2024-12-30T17:03:39.411112image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 189196
 
7.5%
S 180164
 
7.2%
- 171500
 
6.8%
1 135819
 
5.4%
M 134244
 
5.4%
0 125696
 
5.0%
A 119355
 
4.8%
2 118372
 
4.7%
C 100849
 
4.0%
3 83038
 
3.3%
Other values (73) 1150083
45.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2508316
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 189196
 
7.5%
S 180164
 
7.2%
- 171500
 
6.8%
1 135819
 
5.4%
M 134244
 
5.4%
0 125696
 
5.0%
A 119355
 
4.8%
2 118372
 
4.7%
C 100849
 
4.0%
3 83038
 
3.3%
Other values (73) 1150083
45.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2508316
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 189196
 
7.5%
S 180164
 
7.2%
- 171500
 
6.8%
1 135819
 
5.4%
M 134244
 
5.4%
0 125696
 
5.0%
A 119355
 
4.8%
2 118372
 
4.7%
C 100849
 
4.0%
3 83038
 
3.3%
Other values (73) 1150083
45.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2508316
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 189196
 
7.5%
S 180164
 
7.2%
- 171500
 
6.8%
1 135819
 
5.4%
M 134244
 
5.4%
0 125696
 
5.0%
A 119355
 
4.8%
2 118372
 
4.7%
C 100849
 
4.0%
3 83038
 
3.3%
Other values (73) 1150083
45.9%

eventDate
Text

Missing 

Distinct79092
Distinct (%)4.1%
Missing419645
Missing (%)17.8%
Memory size18.0 MiB
2024-12-30T17:03:39.596274image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.989244626
Min length4

Characters and Unicode

Total characters19397315
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14082 ?
Unique (%)0.7%

Sample

1st row1981-04-24
2nd row1952-03-30
3rd row1958-08-06
4th row1900-11
5th row1988-08-20
ValueCountFrequency (%)
1915 2128
 
0.1%
1913 1918
 
0.1%
1916 1707
 
0.1%
1891 1468
 
0.1%
1982-07-21 1436
 
0.1%
1981-07-06 1349
 
0.1%
1923 1342
 
0.1%
1982-11-19 1332
 
0.1%
1880 1329
 
0.1%
1929 1317
 
0.1%
Other values (79082) 1926494
99.2%
2024-12-30T17:03:39.835213image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3722229
19.2%
1 3671534
18.9%
0 2955415
15.2%
9 2451000
12.6%
2 1415301
 
7.3%
8 1113641
 
5.7%
7 900586
 
4.6%
6 896745
 
4.6%
3 759472
 
3.9%
5 731373
 
3.8%
Other values (8) 780019
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 19397315
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 3722229
19.2%
1 3671534
18.9%
0 2955415
15.2%
9 2451000
12.6%
2 1415301
 
7.3%
8 1113641
 
5.7%
7 900586
 
4.6%
6 896745
 
4.6%
3 759472
 
3.9%
5 731373
 
3.8%
Other values (8) 780019
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 19397315
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 3722229
19.2%
1 3671534
18.9%
0 2955415
15.2%
9 2451000
12.6%
2 1415301
 
7.3%
8 1113641
 
5.7%
7 900586
 
4.6%
6 896745
 
4.6%
3 759472
 
3.9%
5 731373
 
3.8%
Other values (8) 780019
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 19397315
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 3722229
19.2%
1 3671534
18.9%
0 2955415
15.2%
9 2451000
12.6%
2 1415301
 
7.3%
8 1113641
 
5.7%
7 900586
 
4.6%
6 896745
 
4.6%
3 759472
 
3.9%
5 731373
 
3.8%
Other values (8) 780019
 
4.0%

eventTime
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

startDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)< 0.1%
Missing669488
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean179.9339288
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:39.898933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile29
Q1109
median184
Q3246
95-th percentile333
Maximum366
Range365
Interquartile range (IQR)137

Descriptive statistics

Standard deviation91.4779416
Coefficient of variation (CV)0.5083974002
Kurtosis-0.8542921363
Mean179.9339288
Median Absolute Deviation (MAD)68
Skewness-0.007716519049
Sum304444069
Variance8368.213799
MonotonicityNot monotonic
2024-12-30T17:03:39.960236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202 8899
 
0.4%
196 7844
 
0.3%
199 7829
 
0.3%
206 7783
 
0.3%
210 7720
 
0.3%
187 7619
 
0.3%
201 7549
 
0.3%
200 7529
 
0.3%
219 7370
 
0.3%
197 7339
 
0.3%
Other values (356) 1614496
68.4%
(Missing) 669488
28.4%
ValueCountFrequency (%)
1 2957
0.1%
2 2303
0.1%
3 2342
0.1%
4 2266
0.1%
5 2716
0.1%
ValueCountFrequency (%)
366 445
 
< 0.1%
365 2006
0.1%
364 2233
0.1%
363 2241
0.1%
362 2341
0.1%

endDayOfYear
Unsupported

Missing  Rejected  Unsupported 

Missing669487
Missing (%)28.4%
Memory size18.0 MiB

year
Real number (ℝ)

Missing 

Distinct301
Distinct (%)< 0.1%
Missing423103
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean1947.049979
Minimum1520
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:40.022240image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1520
5-th percentile1887
Q11917
median1954
Q31975
95-th percentile2001
Maximum2024
Range504
Interquartile range (IQR)58

Descriptive statistics

Standard deviation36.34502819
Coefficient of variation (CV)0.01866671558
Kurtosis-0.4800722973
Mean1947.049979
Median Absolute Deviation (MAD)27
Skewness-0.3651263712
Sum3774087692
Variance1320.961074
MonotonicityNot monotonic
2024-12-30T17:03:40.085028image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1966 36263
 
1.5%
1967 33378
 
1.4%
1964 33172
 
1.4%
1977 31555
 
1.3%
1968 31427
 
1.3%
1965 29410
 
1.2%
1969 28033
 
1.2%
1963 25250
 
1.1%
1970 25083
 
1.1%
1971 24744
 
1.0%
Other values (291) 1640047
69.5%
(Missing) 423103
 
17.9%
ValueCountFrequency (%)
1520 1
< 0.1%
1526 1
< 0.1%
1531 1
< 0.1%
1555 1
< 0.1%
1564 1
< 0.1%
ValueCountFrequency (%)
2024 213
 
< 0.1%
2023 689
< 0.1%
2022 695
< 0.1%
2021 518
< 0.1%
2020 430
< 0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)< 0.1%
Missing542651
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean6.435189635
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:40.136180image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.002319919
Coefficient of variation (CV)0.4665472332
Kurtosis-0.8508125504
Mean6.435189635
Median Absolute Deviation (MAD)2
Skewness-0.01708929575
Sum11704413
Variance9.013924897
MonotonicityNot monotonic
2024-12-30T17:03:40.184183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 238033
10.1%
8 219764
9.3%
6 196911
 
8.3%
5 185253
 
7.8%
4 151950
 
6.4%
9 150297
 
6.4%
3 138711
 
5.9%
10 121081
 
5.1%
2 119259
 
5.1%
11 110527
 
4.7%
Other values (2) 187028
 
7.9%
(Missing) 542651
23.0%
ValueCountFrequency (%)
1 101248
4.3%
2 119259
5.1%
3 138711
5.9%
4 151950
6.4%
5 185253
7.8%
ValueCountFrequency (%)
12 85780
 
3.6%
11 110527
4.7%
10 121081
5.1%
9 150297
6.4%
8 219764
9.3%

day
Unsupported

Missing  Rejected  Unsupported 

Missing762156
Missing (%)32.3%
Memory size18.0 MiB

verbatimEventDate
Text

Missing 

Distinct182341
Distinct (%)16.5%
Missing1255734
Missing (%)53.2%
Memory size18.0 MiB
2024-12-30T17:03:40.342716image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length194
Median length11
Mean length13.22733106
Min length1

Characters and Unicode

Total characters14625870
Distinct characters97
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75345 ?
Unique (%)6.8%

Sample

1st row24 APR 1981
2nd row6 Aug 1958
3rd row24 Jun 1934
4th row24 Mar 1974
5th row23-29 January 1885
ValueCountFrequency (%)
436208
 
11.7%
00 204342
 
5.5%
0000 95954
 
2.6%
aug 94310
 
2.5%
may 93491
 
2.5%
jul 93386
 
2.5%
jun 83860
 
2.3%
apr 78240
 
2.1%
mar 71932
 
1.9%
sep 67673
 
1.8%
Other values (47806) 2396564
64.5%
2024-12-30T17:03:40.577774image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2610229
17.8%
1 1589788
 
10.9%
0 1327938
 
9.1%
9 1155039
 
7.9%
- 1063518
 
7.3%
2 604438
 
4.1%
8 461134
 
3.2%
6 404101
 
2.8%
7 366280
 
2.5%
3 329734
 
2.3%
Other values (87) 4713671
32.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14625870
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2610229
17.8%
1 1589788
 
10.9%
0 1327938
 
9.1%
9 1155039
 
7.9%
- 1063518
 
7.3%
2 604438
 
4.1%
8 461134
 
3.2%
6 404101
 
2.8%
7 366280
 
2.5%
3 329734
 
2.3%
Other values (87) 4713671
32.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14625870
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2610229
17.8%
1 1589788
 
10.9%
0 1327938
 
9.1%
9 1155039
 
7.9%
- 1063518
 
7.3%
2 604438
 
4.1%
8 461134
 
3.2%
6 404101
 
2.8%
7 366280
 
2.5%
3 329734
 
2.3%
Other values (87) 4713671
32.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14625870
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2610229
17.8%
1 1589788
 
10.9%
0 1327938
 
9.1%
9 1155039
 
7.9%
- 1063518
 
7.3%
2 604438
 
4.1%
8 461134
 
3.2%
6 404101
 
2.8%
7 366280
 
2.5%
3 329734
 
2.3%
Other values (87) 4713671
32.2%

habitat
Text

Missing 

Distinct72844
Distinct (%)39.6%
Missing2177638
Missing (%)92.2%
Memory size18.0 MiB
2024-12-30T17:03:40.745507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length795
Median length504
Mean length30.83006849
Min length1

Characters and Unicode

Total characters5667399
Distinct characters131
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57211 ?
Unique (%)31.1%

Sample

1st rowabandoned field
2nd rowIn wet mixed hardwood-pine-podocarpus forest.
3rd rowEcological remarks by collector(s): yes
4th rowRainforest
5th rowTropical dry forest
ValueCountFrequency (%)
forest 43320
 
5.0%
on 24894
 
2.9%
and 21426
 
2.5%
in 20924
 
2.4%
with 15194
 
1.8%
of 14970
 
1.7%
by 14737
 
1.7%
ecological 12371
 
1.4%
remarks 12371
 
1.4%
collector(s 12367
 
1.4%
Other values (24035) 672995
77.8%
2024-12-30T17:03:40.991208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
681742
 
12.0%
e 506903
 
8.9%
a 436200
 
7.7%
o 418533
 
7.4%
r 374871
 
6.6%
s 360402
 
6.4%
n 320370
 
5.7%
i 282376
 
5.0%
t 273985
 
4.8%
l 250910
 
4.4%
Other values (121) 1761107
31.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5667399
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
681742
 
12.0%
e 506903
 
8.9%
a 436200
 
7.7%
o 418533
 
7.4%
r 374871
 
6.6%
s 360402
 
6.4%
n 320370
 
5.7%
i 282376
 
5.0%
t 273985
 
4.8%
l 250910
 
4.4%
Other values (121) 1761107
31.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5667399
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
681742
 
12.0%
e 506903
 
8.9%
a 436200
 
7.7%
o 418533
 
7.4%
r 374871
 
6.6%
s 360402
 
6.4%
n 320370
 
5.7%
i 282376
 
5.0%
t 273985
 
4.8%
l 250910
 
4.4%
Other values (121) 1761107
31.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5667399
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
681742
 
12.0%
e 506903
 
8.9%
a 436200
 
7.7%
o 418533
 
7.4%
r 374871
 
6.6%
s 360402
 
6.4%
n 320370
 
5.7%
i 282376
 
5.0%
t 273985
 
4.8%
l 250910
 
4.4%
Other values (121) 1761107
31.1%

samplingProtocol
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

sampleSizeValue
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

sampleSizeUnit
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

samplingEffort
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean67
Minimum67
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:41.046953image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum67
5-th percentile67
Q167
median67
Q367
95-th percentile67
Maximum67
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean67
Median Absolute Deviation (MAD)0
Skewnessnan
Sum67
Variancenan
MonotonicityStrictly increasing
2024-12-30T17:03:41.089135image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
67 1
 
< 0.1%
(Missing) 2361464
> 99.9%
ValueCountFrequency (%)
67 1
< 0.1%
ValueCountFrequency (%)
67 1
< 0.1%

fieldNotes
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean-63
Minimum-63
Maximum-63
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:41.131182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-63
5-th percentile-63
Q1-63
median-63
Q3-63
95-th percentile-63
Maximum-63
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean-63
Median Absolute Deviation (MAD)0
Skewnessnan
Sum-63
Variancenan
MonotonicityStrictly increasing
2024-12-30T17:03:41.174093image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
-63 1
 
< 0.1%
(Missing) 2361464
> 99.9%
ValueCountFrequency (%)
-63 1
< 0.1%
ValueCountFrequency (%)
-63 1
< 0.1%

eventRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

locationID
Text

Missing 

Distinct50052
Distinct (%)18.1%
Missing2084504
Missing (%)88.3%
Memory size18.0 MiB
2024-12-30T17:03:41.492214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length77797
Median length131
Mean length4.843324511
Min length1

Characters and Unicode

Total characters1341412
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28095 ?
Unique (%)10.1%

Sample

1st row31
2nd rowGS 03383
3rd rowM4
4th row9
5th row68-36
ValueCountFrequency (%)
d 3566
 
1.1%
not 3178
 
1.0%
rec 3070
 
1.0%
4 2339
 
0.7%
1 2281
 
0.7%
rhb 1929
 
0.6%
rfb 1883
 
0.6%
2 1847
 
0.6%
3 1546
 
0.5%
6 1528
 
0.5%
Other values (43774) 294784
92.7%
2024-12-30T17:03:41.747995image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 143532
 
10.7%
2 119590
 
8.9%
0 97991
 
7.3%
- 87059
 
6.5%
3 86532
 
6.5%
5 86435
 
6.4%
4 83135
 
6.2%
6 74491
 
5.6%
7 59619
 
4.4%
8 54830
 
4.1%
Other values (89) 448198
33.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1341412
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 143532
 
10.7%
2 119590
 
8.9%
0 97991
 
7.3%
- 87059
 
6.5%
3 86532
 
6.5%
5 86435
 
6.4%
4 83135
 
6.2%
6 74491
 
5.6%
7 59619
 
4.4%
8 54830
 
4.1%
Other values (89) 448198
33.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1341412
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 143532
 
10.7%
2 119590
 
8.9%
0 97991
 
7.3%
- 87059
 
6.5%
3 86532
 
6.5%
5 86435
 
6.4%
4 83135
 
6.2%
6 74491
 
5.6%
7 59619
 
4.4%
8 54830
 
4.1%
Other values (89) 448198
33.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1341412
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 143532
 
10.7%
2 119590
 
8.9%
0 97991
 
7.3%
- 87059
 
6.5%
3 86532
 
6.5%
5 86435
 
6.4%
4 83135
 
6.2%
6 74491
 
5.6%
7 59619
 
4.4%
8 54830
 
4.1%
Other values (89) 448198
33.4%

higherGeographyID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

higherGeography
Text

Missing 

Distinct48477
Distinct (%)2.1%
Missing73521
Missing (%)3.1%
Memory size18.0 MiB
2024-12-30T17:03:41.907443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length177
Median length138
Mean length40.44185391
Min length4

Characters and Unicode

Total characters92528697
Distinct characters175
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15741 ?
Unique (%)0.7%

Sample

1st rowNorth Atlantic Ocean, Caribbean Sea, Belize
2nd rowNorth America, United States, Tennessee
3rd rowNorth America, United States, West Virginia, Randolph
4th rowUnited States, Georgia, Decatur County
5th rowNorth Atlantic Ocean, Gulf of Mexico, United States
ValueCountFrequency (%)
america 1138436
 
9.2%
north 1106431
 
8.9%
united 860919
 
6.9%
states 853128
 
6.9%
440813
 
3.5%
south 440484
 
3.5%
ocean 430251
 
3.5%
neotropics 407965
 
3.3%
atlantic 224389
 
1.8%
pacific 213983
 
1.7%
Other values (16557) 6300852
50.7%
2024-12-30T17:03:42.141162image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10129707
 
10.9%
a 8943808
 
9.7%
i 6761278
 
7.3%
e 6630282
 
7.2%
t 6497935
 
7.0%
r 5098044
 
5.5%
o 4988699
 
5.4%
, 4761991
 
5.1%
n 4606098
 
5.0%
c 3725687
 
4.0%
Other values (165) 30385168
32.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 92528697
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10129707
 
10.9%
a 8943808
 
9.7%
i 6761278
 
7.3%
e 6630282
 
7.2%
t 6497935
 
7.0%
r 5098044
 
5.5%
o 4988699
 
5.4%
, 4761991
 
5.1%
n 4606098
 
5.0%
c 3725687
 
4.0%
Other values (165) 30385168
32.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 92528697
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10129707
 
10.9%
a 8943808
 
9.7%
i 6761278
 
7.3%
e 6630282
 
7.2%
t 6497935
 
7.0%
r 5098044
 
5.5%
o 4988699
 
5.4%
, 4761991
 
5.1%
n 4606098
 
5.0%
c 3725687
 
4.0%
Other values (165) 30385168
32.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 92528697
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10129707
 
10.9%
a 8943808
 
9.7%
i 6761278
 
7.3%
e 6630282
 
7.2%
t 6497935
 
7.0%
r 5098044
 
5.5%
o 4988699
 
5.4%
, 4761991
 
5.1%
n 4606098
 
5.0%
c 3725687
 
4.0%
Other values (165) 30385168
32.8%

continent
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing411635
Missing (%)17.4%
Memory size18.0 MiB
2024-12-30T17:03:42.208813image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.83902956
Min length4

Characters and Unicode

Total characters21134265
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowASIA
ValueCountFrequency (%)
north_america 1041971
53.4%
south_america 357650
 
18.3%
asia 249516
 
12.8%
oceania 115158
 
5.9%
africa 104098
 
5.3%
europe 75984
 
3.9%
antarctica 5453
 
0.3%
2024-12-30T17:03:42.316732image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 3753145
17.8%
R 2627127
12.4%
I 1873846
8.9%
E 1666747
7.9%
C 1629783
7.7%
O 1590763
7.5%
T 1410527
 
6.7%
H 1399621
 
6.6%
_ 1399621
 
6.6%
M 1399621
 
6.6%
Other values (5) 2383464
11.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21134265
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 3753145
17.8%
R 2627127
12.4%
I 1873846
8.9%
E 1666747
7.9%
C 1629783
7.7%
O 1590763
7.5%
T 1410527
 
6.7%
H 1399621
 
6.6%
_ 1399621
 
6.6%
M 1399621
 
6.6%
Other values (5) 2383464
11.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21134265
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 3753145
17.8%
R 2627127
12.4%
I 1873846
8.9%
E 1666747
7.9%
C 1629783
7.7%
O 1590763
7.5%
T 1410527
 
6.7%
H 1399621
 
6.6%
_ 1399621
 
6.6%
M 1399621
 
6.6%
Other values (5) 2383464
11.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21134265
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 3753145
17.8%
R 2627127
12.4%
I 1873846
8.9%
E 1666747
7.9%
C 1629783
7.7%
O 1590763
7.5%
T 1410527
 
6.7%
H 1399621
 
6.6%
_ 1399621
 
6.6%
M 1399621
 
6.6%
Other values (5) 2383464
11.3%

waterBody
Text

Missing 

Distinct2466
Distinct (%)0.6%
Missing1923752
Missing (%)81.5%
Memory size18.0 MiB
2024-12-30T17:03:42.471509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length75
Median length73
Mean length24.15324196
Min length6

Characters and Unicode

Total characters10572188
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1005 ?
Unique (%)0.2%

Sample

1st rowNorth Atlantic Ocean, Caribbean Sea
2nd rowNorth Atlantic Ocean, Gulf of Mexico
3rd rowNorth Atlantic Ocean, Gulf of Mexico, Galveston Bay
4th rowNorth Pacific Ocean, Gulf of California
5th rowNorth Atlantic Ocean, Gulf of Guinea
ValueCountFrequency (%)
ocean 429242
26.0%
north 326215
19.8%
atlantic 224090
13.6%
pacific 174690
10.6%
of 70763
 
4.3%
sea 70402
 
4.3%
gulf 69641
 
4.2%
south 61315
 
3.7%
mexico 54265
 
3.3%
caribbean 31788
 
1.9%
Other values (1777) 138016
 
8.4%
2024-12-30T17:03:42.713175image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1212714
11.5%
a 1102409
10.4%
c 1096278
10.4%
t 883207
 
8.4%
n 794118
 
7.5%
i 741795
 
7.0%
e 632055
 
6.0%
o 541091
 
5.1%
O 432027
 
4.1%
r 407633
 
3.9%
Other values (63) 2728861
25.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10572188
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1212714
11.5%
a 1102409
10.4%
c 1096278
10.4%
t 883207
 
8.4%
n 794118
 
7.5%
i 741795
 
7.0%
e 632055
 
6.0%
o 541091
 
5.1%
O 432027
 
4.1%
r 407633
 
3.9%
Other values (63) 2728861
25.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10572188
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1212714
11.5%
a 1102409
10.4%
c 1096278
10.4%
t 883207
 
8.4%
n 794118
 
7.5%
i 741795
 
7.0%
e 632055
 
6.0%
o 541091
 
5.1%
O 432027
 
4.1%
r 407633
 
3.9%
Other values (63) 2728861
25.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10572188
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1212714
11.5%
a 1102409
10.4%
c 1096278
10.4%
t 883207
 
8.4%
n 794118
 
7.5%
i 741795
 
7.0%
e 632055
 
6.0%
o 541091
 
5.1%
O 432027
 
4.1%
r 407633
 
3.9%
Other values (63) 2728861
25.8%

islandGroup
Text

Missing 

Distinct655
Distinct (%)1.3%
Missing2309211
Missing (%)97.8%
Memory size18.0 MiB
2024-12-30T17:03:42.835180image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length41
Mean length14.63855399
Min length4

Characters and Unicode

Total characters764923
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)0.3%

Sample

1st rowPelican Cays
2nd rowGreater Antilles
3rd rowStewart Islands
4th rowRalik Chain
5th rowVirgin Islands
ValueCountFrequency (%)
islands 18220
 
16.0%
antilles 8706
 
7.7%
greater 8542
 
7.5%
group 7726
 
6.8%
is 5006
 
4.4%
leeward 2799
 
2.5%
new 2396
 
2.1%
hispaniola 2301
 
2.0%
chain 2114
 
1.9%
virgin 1728
 
1.5%
Other values (552) 54220
47.7%
2024-12-30T17:03:43.015077image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 89318
 
11.7%
s 68956
 
9.0%
61504
 
8.0%
n 56352
 
7.4%
l 54957
 
7.2%
e 53661
 
7.0%
r 46030
 
6.0%
i 39007
 
5.1%
d 31951
 
4.2%
t 28112
 
3.7%
Other values (59) 235075
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 764923
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 89318
 
11.7%
s 68956
 
9.0%
61504
 
8.0%
n 56352
 
7.4%
l 54957
 
7.2%
e 53661
 
7.0%
r 46030
 
6.0%
i 39007
 
5.1%
d 31951
 
4.2%
t 28112
 
3.7%
Other values (59) 235075
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 764923
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 89318
 
11.7%
s 68956
 
9.0%
61504
 
8.0%
n 56352
 
7.4%
l 54957
 
7.2%
e 53661
 
7.0%
r 46030
 
6.0%
i 39007
 
5.1%
d 31951
 
4.2%
t 28112
 
3.7%
Other values (59) 235075
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 764923
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 89318
 
11.7%
s 68956
 
9.0%
61504
 
8.0%
n 56352
 
7.4%
l 54957
 
7.2%
e 53661
 
7.0%
r 46030
 
6.0%
i 39007
 
5.1%
d 31951
 
4.2%
t 28112
 
3.7%
Other values (59) 235075
30.7%

island
Text

Missing 

Distinct4075
Distinct (%)2.6%
Missing2204394
Missing (%)93.3%
Memory size18.0 MiB
2024-12-30T17:03:43.166605image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length47
Median length41
Mean length9.54205423
Min length3

Characters and Unicode

Total characters1498780
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1250 ?
Unique (%)0.8%

Sample

1st rowHonshu
2nd rowLana'i
3rd rowCat Cay
4th rowHawaii
5th rowSumatra
ValueCountFrequency (%)
island 26207
 
10.9%
hispaniola 12814
 
5.3%
cuba 6496
 
2.7%
oahu 6126
 
2.5%
atoll 5648
 
2.3%
luzon 5340
 
2.2%
new 4804
 
2.0%
bermuda 4124
 
1.7%
guinea 3811
 
1.6%
st 3730
 
1.5%
Other values (3177) 162063
67.2%
2024-12-30T17:03:43.376241image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 230928
15.4%
n 107175
 
7.2%
i 100018
 
6.7%
o 93268
 
6.2%
84092
 
5.6%
l 83151
 
5.5%
e 75480
 
5.0%
u 73700
 
4.9%
s 67954
 
4.5%
r 59918
 
4.0%
Other values (77) 523096
34.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1498780
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 230928
15.4%
n 107175
 
7.2%
i 100018
 
6.7%
o 93268
 
6.2%
84092
 
5.6%
l 83151
 
5.5%
e 75480
 
5.0%
u 73700
 
4.9%
s 67954
 
4.5%
r 59918
 
4.0%
Other values (77) 523096
34.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1498780
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 230928
15.4%
n 107175
 
7.2%
i 100018
 
6.7%
o 93268
 
6.2%
84092
 
5.6%
l 83151
 
5.5%
e 75480
 
5.0%
u 73700
 
4.9%
s 67954
 
4.5%
r 59918
 
4.0%
Other values (77) 523096
34.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1498780
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 230928
15.4%
n 107175
 
7.2%
i 100018
 
6.7%
o 93268
 
6.2%
84092
 
5.6%
l 83151
 
5.5%
e 75480
 
5.0%
u 73700
 
4.9%
s 67954
 
4.5%
r 59918
 
4.0%
Other values (77) 523096
34.9%

countryCode
Text

Missing 

Distinct247
Distinct (%)< 0.1%
Missing95309
Missing (%)4.0%
Memory size18.0 MiB
2024-12-30T17:03:43.536664image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4532312
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowBZ
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 845739
37.3%
mx 117278
 
5.2%
br 95212
 
4.2%
ph 68631
 
3.0%
co 59012
 
2.6%
ca 50585
 
2.2%
pa 48976
 
2.2%
ve 43923
 
1.9%
cn 40185
 
1.8%
pe 39643
 
1.7%
Other values (237) 856972
37.8%
2024-12-30T17:03:43.745530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 922312
20.3%
S 901985
19.9%
C 277772
 
6.1%
P 257292
 
5.7%
M 212476
 
4.7%
R 196291
 
4.3%
A 194321
 
4.3%
B 172653
 
3.8%
E 158329
 
3.5%
H 122627
 
2.7%
Other values (16) 1116254
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4532312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 922312
20.3%
S 901985
19.9%
C 277772
 
6.1%
P 257292
 
5.7%
M 212476
 
4.7%
R 196291
 
4.3%
A 194321
 
4.3%
B 172653
 
3.8%
E 158329
 
3.5%
H 122627
 
2.7%
Other values (16) 1116254
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4532312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 922312
20.3%
S 901985
19.9%
C 277772
 
6.1%
P 257292
 
5.7%
M 212476
 
4.7%
R 196291
 
4.3%
A 194321
 
4.3%
B 172653
 
3.8%
E 158329
 
3.5%
H 122627
 
2.7%
Other values (16) 1116254
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4532312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 922312
20.3%
S 901985
19.9%
C 277772
 
6.1%
P 257292
 
5.7%
M 212476
 
4.7%
R 196291
 
4.3%
A 194321
 
4.3%
B 172653
 
3.8%
E 158329
 
3.5%
H 122627
 
2.7%
Other values (16) 1116254
24.6%

stateProvince
Text

Missing 

Distinct7056
Distinct (%)0.4%
Missing637063
Missing (%)27.0%
Memory size18.0 MiB
2024-12-30T17:03:43.906114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length52
Mean length9.275840552
Min length1

Characters and Unicode

Total characters15995278
Distinct characters150
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1731 ?
Unique (%)0.1%

Sample

1st rowTennessee
2nd rowWest Virginia
3rd rowGeorgia
4th rowMaine
5th rowTexas
ValueCountFrequency (%)
california 92210
 
4.0%
florida 79202
 
3.5%
virginia 63444
 
2.8%
carolina 49684
 
2.2%
new 49642
 
2.2%
north 41844
 
1.8%
texas 40438
 
1.8%
alaska 39419
 
1.7%
massachusetts 36351
 
1.6%
maryland 30762
 
1.3%
Other values (5148) 1769142
77.2%
2024-12-30T17:03:44.145407image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2411519
15.1%
i 1368926
 
8.6%
n 1172663
 
7.3%
o 1168856
 
7.3%
r 1039407
 
6.5%
e 843433
 
5.3%
s 754672
 
4.7%
l 682298
 
4.3%
t 604614
 
3.8%
567736
 
3.5%
Other values (140) 5381154
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15995278
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2411519
15.1%
i 1368926
 
8.6%
n 1172663
 
7.3%
o 1168856
 
7.3%
r 1039407
 
6.5%
e 843433
 
5.3%
s 754672
 
4.7%
l 682298
 
4.3%
t 604614
 
3.8%
567736
 
3.5%
Other values (140) 5381154
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15995278
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2411519
15.1%
i 1368926
 
8.6%
n 1172663
 
7.3%
o 1168856
 
7.3%
r 1039407
 
6.5%
e 843433
 
5.3%
s 754672
 
4.7%
l 682298
 
4.3%
t 604614
 
3.8%
567736
 
3.5%
Other values (140) 5381154
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15995278
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2411519
15.1%
i 1368926
 
8.6%
n 1172663
 
7.3%
o 1168856
 
7.3%
r 1039407
 
6.5%
e 843433
 
5.3%
s 754672
 
4.7%
l 682298
 
4.3%
t 604614
 
3.8%
567736
 
3.5%
Other values (140) 5381154
33.6%

county
Text

Missing 

Distinct13641
Distinct (%)2.5%
Missing1825427
Missing (%)77.3%
Memory size18.0 MiB
2024-12-30T17:03:44.281646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length45
Mean length10.24671572
Min length1

Characters and Unicode

Total characters5492629
Distinct characters127
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4083 ?
Unique (%)0.8%

Sample

1st rowRandolph
2nd rowDecatur County
3rd rowPenobscot
4th rowGalveston County
5th rowDona Ana
ValueCountFrequency (%)
county 89628
 
10.8%
not 33486
 
4.0%
stated 33486
 
4.0%
san 13117
 
1.6%
prince 8967
 
1.1%
montgomery 8280
 
1.0%
district 8120
 
1.0%
santa 7340
 
0.9%
honolulu 7298
 
0.9%
6994
 
0.8%
Other values (9747) 611159
73.8%
2024-12-30T17:03:44.478796image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 521111
 
9.5%
o 447666
 
8.2%
n 426871
 
7.8%
e 416438
 
7.6%
t 377430
 
6.9%
r 296404
 
5.4%
291837
 
5.3%
i 275802
 
5.0%
u 235367
 
4.3%
l 211481
 
3.9%
Other values (117) 1992222
36.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5492629
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 521111
 
9.5%
o 447666
 
8.2%
n 426871
 
7.8%
e 416438
 
7.6%
t 377430
 
6.9%
r 296404
 
5.4%
291837
 
5.3%
i 275802
 
5.0%
u 235367
 
4.3%
l 211481
 
3.9%
Other values (117) 1992222
36.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5492629
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 521111
 
9.5%
o 447666
 
8.2%
n 426871
 
7.8%
e 416438
 
7.6%
t 377430
 
6.9%
r 296404
 
5.4%
291837
 
5.3%
i 275802
 
5.0%
u 235367
 
4.3%
l 211481
 
3.9%
Other values (117) 1992222
36.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5492629
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 521111
 
9.5%
o 447666
 
8.2%
n 426871
 
7.8%
e 416438
 
7.6%
t 377430
 
6.9%
r 296404
 
5.4%
291837
 
5.3%
i 275802
 
5.0%
u 235367
 
4.3%
l 211481
 
3.9%
Other values (117) 1992222
36.3%

municipality
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean-53.33
Minimum-53.33
Maximum-53.33
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:44.535800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-53.33
5-th percentile-53.33
Q1-53.33
median-53.33
Q3-53.33
95-th percentile-53.33
Maximum-53.33
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean-53.33
Median Absolute Deviation (MAD)0
Skewnessnan
Sum-53.33
Variancenan
MonotonicityStrictly increasing
2024-12-30T17:03:44.580432image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
-53.33 1
 
< 0.1%
(Missing) 2361464
> 99.9%
ValueCountFrequency (%)
-53.33 1
< 0.1%
ValueCountFrequency (%)
-53.33 1
< 0.1%

locality
Text

Missing 

Distinct924335
Distinct (%)45.7%
Missing337166
Missing (%)14.3%
Memory size18.0 MiB
2024-12-30T17:03:44.866244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21025
Median length366
Mean length40.18539603
Min length1

Characters and Unicode

Total characters81347257
Distinct characters327
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique735981 ?
Unique (%)36.4%

Sample

1st rowCarrie Bow Cay, Spur And Groove Zone
2nd rowEastern edge of Nashville, Davidson County.
3rd rowMonongahela National Forest, 1.2-1.4 mi (by road) W of Bear Heaven Campground, on road to Bickle Knob
4th rowHales Landing, Flint River about 7 miles below Bainbridge, basal Chattahoochee Formation, Oligocene, Vicksburgian
5th rowOrono
ValueCountFrequency (%)
of 675679
 
5.1%
de 173408
 
1.3%
island 171411
 
1.3%
km 144838
 
1.1%
on 127182
 
1.0%
near 121461
 
0.9%
the 114484
 
0.9%
road 113754
 
0.9%
mi 107843
 
0.8%
and 105626
 
0.8%
Other values (326827) 11338924
85.9%
2024-12-30T17:03:45.217763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11169151
 
13.7%
a 7430312
 
9.1%
e 5543946
 
6.8%
o 5385204
 
6.6%
n 4533100
 
5.6%
i 4112258
 
5.1%
r 3955530
 
4.9%
t 3617014
 
4.4%
l 2965975
 
3.6%
s 2859066
 
3.5%
Other values (317) 29775701
36.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 81347257
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
11169151
 
13.7%
a 7430312
 
9.1%
e 5543946
 
6.8%
o 5385204
 
6.6%
n 4533100
 
5.6%
i 4112258
 
5.1%
r 3955530
 
4.9%
t 3617014
 
4.4%
l 2965975
 
3.6%
s 2859066
 
3.5%
Other values (317) 29775701
36.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 81347257
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
11169151
 
13.7%
a 7430312
 
9.1%
e 5543946
 
6.8%
o 5385204
 
6.6%
n 4533100
 
5.6%
i 4112258
 
5.1%
r 3955530
 
4.9%
t 3617014
 
4.4%
l 2965975
 
3.6%
s 2859066
 
3.5%
Other values (317) 29775701
36.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 81347257
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
11169151
 
13.7%
a 7430312
 
9.1%
e 5543946
 
6.8%
o 5385204
 
6.6%
n 4533100
 
5.6%
i 4112258
 
5.1%
r 3955530
 
4.9%
t 3617014
 
4.4%
l 2965975
 
3.6%
s 2859066
 
3.5%
Other values (317) 29775701
36.6%

verbatimLocality
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

verbatimElevation
Text

Missing 

Distinct2886
Distinct (%)4.2%
Missing2293080
Missing (%)97.1%
Memory size18.0 MiB
2024-12-30T17:03:45.375830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length152
Median length124
Mean length7.501996052
Min length1

Characters and Unicode

Total characters513024
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique752 ?
Unique (%)1.1%

Sample

1st row3600 (3440-3760) ft
2nd row~1800 ft.
3rd row80 ft
4th row160 m
5th row150 m
ValueCountFrequency (%)
ft 49451
34.2%
m 16017
 
11.1%
ca 3567
 
2.5%
feet 1112
 
0.8%
200 1103
 
0.8%
1100-1350 1002
 
0.7%
10 898
 
0.6%
20 771
 
0.5%
3400 723
 
0.5%
3500 707
 
0.5%
Other values (1929) 69115
47.8%
2024-12-30T17:03:45.678694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102042
19.9%
76081
14.8%
t 52717
10.3%
f 51306
10.0%
1 26577
 
5.2%
3 25497
 
5.0%
2 24429
 
4.8%
4 22152
 
4.3%
5 20591
 
4.0%
m 17094
 
3.3%
Other values (67) 94538
18.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 513024
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 102042
19.9%
76081
14.8%
t 52717
10.3%
f 51306
10.0%
1 26577
 
5.2%
3 25497
 
5.0%
2 24429
 
4.8%
4 22152
 
4.3%
5 20591
 
4.0%
m 17094
 
3.3%
Other values (67) 94538
18.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 513024
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 102042
19.9%
76081
14.8%
t 52717
10.3%
f 51306
10.0%
1 26577
 
5.2%
3 25497
 
5.0%
2 24429
 
4.8%
4 22152
 
4.3%
5 20591
 
4.0%
m 17094
 
3.3%
Other values (67) 94538
18.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 513024
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 102042
19.9%
76081
14.8%
t 52717
10.3%
f 51306
10.0%
1 26577
 
5.2%
3 25497
 
5.0%
2 24429
 
4.8%
4 22152
 
4.3%
5 20591
 
4.0%
m 17094
 
3.3%
Other values (67) 94538
18.4%

verticalDatum
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

verbatimDepth
Text

Missing 

Distinct852
Distinct (%)5.9%
Missing2346998
Missing (%)99.4%
Memory size18.0 MiB
2024-12-30T17:03:45.849090image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length91
Median length86
Mean length8.728692887
Min length1

Characters and Unicode

Total characters126278
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)3.0%

Sample

1st rowLittoral
2nd row00000000, 00000013
3rd rowpenetration depth: 15cm
4th row1 ms ca.
5th rowIntertidal
ValueCountFrequency (%)
ca 6538
29.0%
intertidal 3133
13.9%
surface 1656
 
7.3%
recorded 744
 
3.3%
depths 742
 
3.3%
multiple 737
 
3.3%
depth 503
 
2.2%
at 295
 
1.3%
0 292
 
1.3%
0-300 287
 
1.3%
Other values (775) 7609
33.8%
2024-12-30T17:03:46.090066image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12027
 
9.5%
t 10705
 
8.5%
e 10427
 
8.3%
c 8271
 
6.5%
8069
 
6.4%
r 7525
 
6.0%
d 6564
 
5.2%
. 6041
 
4.8%
0 6026
 
4.8%
l 5544
 
4.4%
Other values (68) 45079
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 126278
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12027
 
9.5%
t 10705
 
8.5%
e 10427
 
8.3%
c 8271
 
6.5%
8069
 
6.4%
r 7525
 
6.0%
d 6564
 
5.2%
. 6041
 
4.8%
0 6026
 
4.8%
l 5544
 
4.4%
Other values (68) 45079
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 126278
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12027
 
9.5%
t 10705
 
8.5%
e 10427
 
8.3%
c 8271
 
6.5%
8069
 
6.4%
r 7525
 
6.0%
d 6564
 
5.2%
. 6041
 
4.8%
0 6026
 
4.8%
l 5544
 
4.4%
Other values (68) 45079
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 126278
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12027
 
9.5%
t 10705
 
8.5%
e 10427
 
8.3%
c 8271
 
6.5%
8069
 
6.4%
r 7525
 
6.0%
d 6564
 
5.2%
. 6041
 
4.8%
0 6026
 
4.8%
l 5544
 
4.4%
Other values (68) 45079
35.7%

minimumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

maximumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

locationAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

locationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

decimalLatitude
Real number (ℝ)

Missing 

Distinct97853
Distinct (%)13.7%
Missing1649758
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean18.26121176
Minimum-87.55
Maximum90
Zeros144
Zeros (%)< 0.1%
Negative138202
Negative (%)5.9%
Memory size18.0 MiB
2024-12-30T17:03:46.154521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-87.55
5-th percentile-29
Q15.175
median25.58
Q337.6212
95-th percentile45.92035
Maximum90
Range177.55
Interquartile range (IQR)32.4462

Descriptive statistics

Standard deviation25.30763668
Coefficient of variation (CV)1.385868419
Kurtosis1.460366745
Mean18.26121176
Median Absolute Deviation (MAD)14.4133
Skewness-1.10215697
Sum12996632.24
Variance640.4764742
MonotonicityNot monotonic
2024-12-30T17:03:46.211521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.58 2624
 
0.1%
40.6583 2215
 
0.1%
26.17 1834
 
0.1%
26.5 1343
 
0.1%
39.6891 1261
 
0.1%
38.9694 1127
 
< 0.1%
39.6306 1069
 
< 0.1%
38.895 1015
 
< 0.1%
26.97 1004
 
< 0.1%
60.75 991
 
< 0.1%
Other values (97843) 697224
29.5%
(Missing) 1649758
69.9%
ValueCountFrequency (%)
-87.55 1
 
< 0.1%
-82.375 1
 
< 0.1%
-80.625 1
 
< 0.1%
-78.9167 1
 
< 0.1%
-78.5 3
< 0.1%
ValueCountFrequency (%)
90 1
 
< 0.1%
89.65 2
 
< 0.1%
89.4074 1
 
< 0.1%
89.208 5
< 0.1%
86.6028 1
 
< 0.1%

decimalLongitude
Real number (ℝ)

Missing 

Distinct102753
Distinct (%)14.4%
Missing1649758
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean-49.51795233
Minimum-180
Maximum180
Zeros45
Zeros (%)< 0.1%
Negative580730
Negative (%)24.6%
Memory size18.0 MiB
2024-12-30T17:03:46.269131image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-180
5-th percentile-124.0378656
Q1-84.4201
median-76.62
Q3-56.3833
95-th percentile129.865
Maximum180
Range360
Interquartile range (IQR)28.0368

Descriptive statistics

Standard deviation76.40729115
Coefficient of variation (CV)-1.543022026
Kurtosis1.438064233
Mean-49.51795233
Median Absolute Deviation (MAD)13.4045
Skewness1.5121654
Sum-35242273.3
Variance5838.07414
MonotonicityNot monotonic
2024-12-30T17:03:46.326130image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-80.1 2639
 
0.1%
-105.644 1278
 
0.1%
127.848 1115
 
< 0.1%
-88.08 1095
 
< 0.1%
-77.4714 1069
 
< 0.1%
-67.7683 1046
 
< 0.1%
-139.5 992
 
< 0.1%
-77.0367 986
 
< 0.1%
-80.13 977
 
< 0.1%
-77.1767 933
 
< 0.1%
Other values (102743) 699577
29.6%
(Missing) 1649758
69.9%
ValueCountFrequency (%)
-180 4
< 0.1%
-179.994 1
 
< 0.1%
-179.98 4
< 0.1%
-179.97 6
< 0.1%
-179.954 1
 
< 0.1%
ValueCountFrequency (%)
180 5
 
< 0.1%
179.994 1
 
< 0.1%
179.98 18
< 0.1%
179.967 1
 
< 0.1%
179.952 1
 
< 0.1%

coordinateUncertaintyInMeters
Real number (ℝ)

Missing  Skewed 

Distinct5438
Distinct (%)12.6%
Missing2318343
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean8365.260956
Minimum0.05
Maximum3884420
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:46.387187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile156.36
Q1901.315
median2708.53
Q36109.07
95-th percentile30443.115
Maximum3884420
Range3884419.95
Interquartile range (IQR)5207.755

Descriptive statistics

Standard deviation39650.32164
Coefficient of variation (CV)4.73987863
Kurtosis2464.643954
Mean8365.260956
Median Absolute Deviation (MAD)2146.86
Skewness35.60903197
Sum360726782.9
Variance1572148006
MonotonicityNot monotonic
2024-12-30T17:03:46.455319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3036 447
 
< 0.1%
100 377
 
< 0.1%
347.62 374
 
< 0.1%
500 363
 
< 0.1%
16000 330
 
< 0.1%
186.68 323
 
< 0.1%
1000 321
 
< 0.1%
4615 287
 
< 0.1%
1066 266
 
< 0.1%
5615 259
 
< 0.1%
Other values (5428) 39775
 
1.7%
(Missing) 2318343
98.2%
ValueCountFrequency (%)
0.05 14
 
< 0.1%
1.02 7
 
< 0.1%
4 1
 
< 0.1%
5 40
< 0.1%
6 9
 
< 0.1%
ValueCountFrequency (%)
3884420 1
 
< 0.1%
1501015 2
< 0.1%
1465107 1
 
< 0.1%
1158937 2
< 0.1%
1113155 3
< 0.1%

coordinatePrecision
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

pointRadiusSpatialFit
Real number (ℝ)

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3529876
Minimum3190721
Maximum3869031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:46.508321image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum3190721
5-th percentile3224636.5
Q13360298.5
median3529876
Q33699453.5
95-th percentile3835115.5
Maximum3869031
Range678310
Interquartile range (IQR)339155

Descriptive statistics

Standard deviation479637.6007
Coefficient of variation (CV)0.1358794475
Kurtosisnan
Mean3529876
Median Absolute Deviation (MAD)339155
Skewnessnan
Sum7059752
Variance2.30052228 × 1011
MonotonicityStrictly increasing
2024-12-30T17:03:46.555356image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
3190721 1
 
< 0.1%
3869031 1
 
< 0.1%
(Missing) 2361463
> 99.9%
ValueCountFrequency (%)
3190721 1
< 0.1%
3869031 1
< 0.1%
ValueCountFrequency (%)
3869031 1
< 0.1%
3190721 1
< 0.1%
Distinct8
Distinct (%)< 0.1%
Missing2103311
Missing (%)89.1%
Memory size18.0 MiB
2024-12-30T17:03:46.615061image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.71798229
Min length3

Characters and Unicode

Total characters5864738
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 255841
33.4%
minutes 249742
32.6%
seconds 249742
32.6%
decimal 6099
 
0.8%
township 1828
 
0.2%
range 1828
 
0.2%
utm 195
 
< 0.1%
marsden 143
 
< 0.1%
square 143
 
< 0.1%
unknown 140
 
< 0.1%
2024-12-30T17:03:46.734429image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1275220
21.7%
s 757296
12.9%
507554
 
8.7%
n 503703
 
8.6%
g 257669
 
4.4%
i 257669
 
4.4%
r 256127
 
4.4%
d 255978
 
4.4%
D 255854
 
4.4%
c 255841
 
4.4%
Other values (18) 1281827
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5864738
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1275220
21.7%
s 757296
12.9%
507554
 
8.7%
n 503703
 
8.6%
g 257669
 
4.4%
i 257669
 
4.4%
r 256127
 
4.4%
d 255978
 
4.4%
D 255854
 
4.4%
c 255841
 
4.4%
Other values (18) 1281827
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5864738
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1275220
21.7%
s 757296
12.9%
507554
 
8.7%
n 503703
 
8.6%
g 257669
 
4.4%
i 257669
 
4.4%
r 256127
 
4.4%
d 255978
 
4.4%
D 255854
 
4.4%
c 255841
 
4.4%
Other values (18) 1281827
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5864738
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1275220
21.7%
s 757296
12.9%
507554
 
8.7%
n 503703
 
8.6%
g 257669
 
4.4%
i 257669
 
4.4%
r 256127
 
4.4%
d 255978
 
4.4%
D 255854
 
4.4%
c 255841
 
4.4%
Other values (18) 1281827
21.9%

verbatimSRS
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

footprintWKT
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

footprintSRS
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

footprintSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

georeferencedBy
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:46.794570image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length19.5
Mean length19.5
Min length10

Characters and Unicode

Total characters39
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDrosera L.
2nd rowMiconia coronata (Bonpl.) DC.
ValueCountFrequency (%)
drosera 1
16.7%
l 1
16.7%
miconia 1
16.7%
coronata 1
16.7%
bonpl 1
16.7%
dc 1
16.7%
2024-12-30T17:03:46.908780image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 5
12.8%
a 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
. 3
 
7.7%
n 3
 
7.7%
c 2
 
5.1%
D 2
 
5.1%
i 2
 
5.1%
s 1
 
2.6%
Other values (10) 10
25.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 5
12.8%
a 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
. 3
 
7.7%
n 3
 
7.7%
c 2
 
5.1%
D 2
 
5.1%
i 2
 
5.1%
s 1
 
2.6%
Other values (10) 10
25.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 5
12.8%
a 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
. 3
 
7.7%
n 3
 
7.7%
c 2
 
5.1%
D 2
 
5.1%
i 2
 
5.1%
s 1
 
2.6%
Other values (10) 10
25.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 5
12.8%
a 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
. 3
 
7.7%
n 3
 
7.7%
c 2
 
5.1%
D 2
 
5.1%
i 2
 
5.1%
s 1
 
2.6%
Other values (10) 10
25.6%

georeferencedDate
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

georeferenceProtocol
Text

Missing 

Distinct2390
Distinct (%)0.8%
Missing2055864
Missing (%)87.1%
Memory size18.0 MiB
2024-12-30T17:03:47.046061image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length302
Median length300
Mean length25.56020105
Min length3

Characters and Unicode

Total characters7811223
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique794 ?
Unique (%)0.3%

Sample

1st rowunknown, from legacy
2nd rowGEOLocate
3rd rowArcGIS software with data from New Mexico Resource Geographic Information System Program (http://rgis.unm.edu) and other inhouse resources (historical maps aiding with name changes), MaNIS/HerpNET/ORNIS Georeferencing Guidelines
4th rowGoogle Earth
5th rowAlexandria Digital Library Gazetteer, MaNIS/HerpNET/ORNIS Georeferencing Guidelines
ValueCountFrequency (%)
from 130830
 
12.9%
unknown 129199
 
12.8%
legacy 128679
 
12.7%
google 54944
 
5.4%
earth 40154
 
4.0%
geolocate 36281
 
3.6%
georeferencing 34967
 
3.5%
manis/herpnet/ornis 34312
 
3.4%
guidelines 34310
 
3.4%
gazetteer 20215
 
2.0%
Other values (2833) 367939
36.4%
2024-12-30T17:03:47.259182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
706229
 
9.0%
e 670307
 
8.6%
o 567440
 
7.3%
n 560593
 
7.2%
a 452507
 
5.8%
r 410585
 
5.3%
l 272912
 
3.5%
g 263573
 
3.4%
G 248223
 
3.2%
c 246755
 
3.2%
Other values (69) 3412099
43.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7811223
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
706229
 
9.0%
e 670307
 
8.6%
o 567440
 
7.3%
n 560593
 
7.2%
a 452507
 
5.8%
r 410585
 
5.3%
l 272912
 
3.5%
g 263573
 
3.4%
G 248223
 
3.2%
c 246755
 
3.2%
Other values (69) 3412099
43.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7811223
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
706229
 
9.0%
e 670307
 
8.6%
o 567440
 
7.3%
n 560593
 
7.2%
a 452507
 
5.8%
r 410585
 
5.3%
l 272912
 
3.5%
g 263573
 
3.4%
G 248223
 
3.2%
c 246755
 
3.2%
Other values (69) 3412099
43.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7811223
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
706229
 
9.0%
e 670307
 
8.6%
o 567440
 
7.3%
n 560593
 
7.2%
a 452507
 
5.8%
r 410585
 
5.3%
l 272912
 
3.5%
g 263573
 
3.4%
G 248223
 
3.2%
c 246755
 
3.2%
Other values (69) 3412099
43.7%

georeferenceSources
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

georeferenceRemarks
Text

Missing 

Distinct4928
Distinct (%)9.5%
Missing2309420
Missing (%)97.8%
Memory size18.0 MiB
2024-12-30T17:03:47.423185image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length182
Median length126
Mean length21.75194543
Min length1

Characters and Unicode

Total characters1132080
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2477 ?
Unique (%)4.8%

Sample

1st rowLocality extent = 400 m
2nd rowLocality extent = 0.6
3rd rowLocality extent = 1.059 mi.
4th rowLocality extent = 800 m
5th rowCoordinate Uncertainty In Meters: 44967
ValueCountFrequency (%)
locality 34471
16.6%
34367
16.6%
extent 34334
16.6%
mi 10224
 
4.9%
ca 4838
 
2.3%
km 2968
 
1.4%
approximate 2550
 
1.2%
in 2301
 
1.1%
coordinate 2093
 
1.0%
meters 2084
 
1.0%
Other values (5048) 76887
37.1%
2024-12-30T17:03:47.669542image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155072
 
13.7%
t 128158
 
11.3%
e 96698
 
8.5%
a 61605
 
5.4%
i 59118
 
5.2%
o 54266
 
4.8%
n 53362
 
4.7%
l 42258
 
3.7%
c 39954
 
3.5%
. 39122
 
3.5%
Other values (71) 402467
35.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1132080
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
155072
 
13.7%
t 128158
 
11.3%
e 96698
 
8.5%
a 61605
 
5.4%
i 59118
 
5.2%
o 54266
 
4.8%
n 53362
 
4.7%
l 42258
 
3.7%
c 39954
 
3.5%
. 39122
 
3.5%
Other values (71) 402467
35.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1132080
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
155072
 
13.7%
t 128158
 
11.3%
e 96698
 
8.5%
a 61605
 
5.4%
i 59118
 
5.2%
o 54266
 
4.8%
n 53362
 
4.7%
l 42258
 
3.7%
c 39954
 
3.5%
. 39122
 
3.5%
Other values (71) 402467
35.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1132080
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
155072
 
13.7%
t 128158
 
11.3%
e 96698
 
8.5%
a 61605
 
5.4%
i 59118
 
5.2%
o 54266
 
4.8%
n 53362
 
4.7%
l 42258
 
3.7%
c 39954
 
3.5%
. 39122
 
3.5%
Other values (71) 402467
35.6%

geologicalContextID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

earliestEonOrLowestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB
Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:47.738545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length67
Median length59
Mean length59
Min length51

Characters and Unicode

Total characters118
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPlantae, Dicotyledonae, Caryophyllales, Droseraceae
2nd rowPlantae, Dicotyledonae, Myrtales, Melastomataceae, Melastomatoideae
ValueCountFrequency (%)
plantae 2
22.2%
dicotyledonae 2
22.2%
caryophyllales 1
11.1%
droseraceae 1
11.1%
myrtales 1
11.1%
melastomataceae 1
11.1%
melastomatoideae 1
11.1%
2024-12-30T17:03:47.858360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 18
15.3%
e 17
14.4%
l 10
 
8.5%
o 9
 
7.6%
t 9
 
7.6%
7
 
5.9%
, 7
 
5.9%
y 5
 
4.2%
s 5
 
4.2%
r 4
 
3.4%
Other values (11) 27
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 118
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 18
15.3%
e 17
14.4%
l 10
 
8.5%
o 9
 
7.6%
t 9
 
7.6%
7
 
5.9%
, 7
 
5.9%
y 5
 
4.2%
s 5
 
4.2%
r 4
 
3.4%
Other values (11) 27
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 118
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 18
15.3%
e 17
14.4%
l 10
 
8.5%
o 9
 
7.6%
t 9
 
7.6%
7
 
5.9%
, 7
 
5.9%
y 5
 
4.2%
s 5
 
4.2%
r 4
 
3.4%
Other values (11) 27
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 118
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 18
15.3%
e 17
14.4%
l 10
 
8.5%
o 9
 
7.6%
t 9
 
7.6%
7
 
5.9%
, 7
 
5.9%
y 5
 
4.2%
s 5
 
4.2%
r 4
 
3.4%
Other values (11) 27
22.9%

earliestEraOrLowestErathem
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:47.910358image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlantae
2nd rowPlantae
ValueCountFrequency (%)
plantae 2
100.0%
2024-12-30T17:03:48.003571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

latestEraOrHighestErathem
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:48.060582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTracheophyta
2nd rowTracheophyta
ValueCountFrequency (%)
tracheophyta 2
100.0%
2024-12-30T17:03:48.164449image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 4
16.7%
a 4
16.7%
r 2
8.3%
T 2
8.3%
c 2
8.3%
e 2
8.3%
o 2
8.3%
p 2
8.3%
y 2
8.3%
t 2
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 4
16.7%
a 4
16.7%
r 2
8.3%
T 2
8.3%
c 2
8.3%
e 2
8.3%
o 2
8.3%
p 2
8.3%
y 2
8.3%
t 2
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 4
16.7%
a 4
16.7%
r 2
8.3%
T 2
8.3%
c 2
8.3%
e 2
8.3%
o 2
8.3%
p 2
8.3%
y 2
8.3%
t 2
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 4
16.7%
a 4
16.7%
r 2
8.3%
T 2
8.3%
c 2
8.3%
e 2
8.3%
o 2
8.3%
p 2
8.3%
y 2
8.3%
t 2
8.3%

earliestPeriodOrLowestSystem
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:48.223688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters26
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMagnoliopsida
2nd rowMagnoliopsida
ValueCountFrequency (%)
magnoliopsida 2
100.0%
2024-12-30T17:03:48.325861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
15.4%
o 4
15.4%
i 4
15.4%
M 2
7.7%
n 2
7.7%
g 2
7.7%
l 2
7.7%
p 2
7.7%
s 2
7.7%
d 2
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
15.4%
o 4
15.4%
i 4
15.4%
M 2
7.7%
n 2
7.7%
g 2
7.7%
l 2
7.7%
p 2
7.7%
s 2
7.7%
d 2
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
15.4%
o 4
15.4%
i 4
15.4%
M 2
7.7%
n 2
7.7%
g 2
7.7%
l 2
7.7%
p 2
7.7%
s 2
7.7%
d 2
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
15.4%
o 4
15.4%
i 4
15.4%
M 2
7.7%
n 2
7.7%
g 2
7.7%
l 2
7.7%
p 2
7.7%
s 2
7.7%
d 2
7.7%
Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:48.454415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11
Min length8

Characters and Unicode

Total characters22
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowCaryophyllales
2nd rowMyrtales
ValueCountFrequency (%)
caryophyllales 1
50.0%
myrtales 1
50.0%
2024-12-30T17:03:48.565551image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 4
18.2%
a 3
13.6%
y 3
13.6%
r 2
9.1%
s 2
9.1%
e 2
9.1%
C 1
 
4.5%
o 1
 
4.5%
h 1
 
4.5%
p 1
 
4.5%
Other values (2) 2
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 4
18.2%
a 3
13.6%
y 3
13.6%
r 2
9.1%
s 2
9.1%
e 2
9.1%
C 1
 
4.5%
o 1
 
4.5%
h 1
 
4.5%
p 1
 
4.5%
Other values (2) 2
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 4
18.2%
a 3
13.6%
y 3
13.6%
r 2
9.1%
s 2
9.1%
e 2
9.1%
C 1
 
4.5%
o 1
 
4.5%
h 1
 
4.5%
p 1
 
4.5%
Other values (2) 2
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 22
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 4
18.2%
a 3
13.6%
y 3
13.6%
r 2
9.1%
s 2
9.1%
e 2
9.1%
C 1
 
4.5%
o 1
 
4.5%
h 1
 
4.5%
p 1
 
4.5%
Other values (2) 2
9.1%

earliestEpochOrLowestSeries
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean5410907
Minimum5410907
Maximum5410907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:48.612230image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum5410907
5-th percentile5410907
Q15410907
median5410907
Q35410907
95-th percentile5410907
Maximum5410907
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean5410907
Median Absolute Deviation (MAD)0
Skewnessnan
Sum5410907
Variancenan
MonotonicityStrictly increasing
2024-12-30T17:03:48.655280image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
5410907 1
 
< 0.1%
(Missing) 2361464
> 99.9%
ValueCountFrequency (%)
5410907 1
< 0.1%
ValueCountFrequency (%)
5410907 1
< 0.1%
Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:48.707283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length13
Mean length13
Min length11

Characters and Unicode

Total characters26
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDroseraceae
2nd rowMelastomataceae
ValueCountFrequency (%)
droseraceae 1
50.0%
melastomataceae 1
50.0%
2024-12-30T17:03:48.822294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6
23.1%
a 6
23.1%
r 2
 
7.7%
t 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
c 2
 
7.7%
D 1
 
3.8%
M 1
 
3.8%
l 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 6
23.1%
a 6
23.1%
r 2
 
7.7%
t 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
c 2
 
7.7%
D 1
 
3.8%
M 1
 
3.8%
l 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 6
23.1%
a 6
23.1%
r 2
 
7.7%
t 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
c 2
 
7.7%
D 1
 
3.8%
M 1
 
3.8%
l 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 6
23.1%
a 6
23.1%
r 2
 
7.7%
t 2
 
7.7%
o 2
 
7.7%
s 2
 
7.7%
c 2
 
7.7%
D 1
 
3.8%
M 1
 
3.8%
l 1
 
3.8%

earliestAgeOrLowestStage
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

latestAgeOrHighestStage
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

lowestBiostratigraphicZone
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:48.868800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowScharf, U.
ValueCountFrequency (%)
scharf 1
50.0%
u 1
50.0%
2024-12-30T17:03:48.964612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1
10.0%
c 1
10.0%
h 1
10.0%
a 1
10.0%
r 1
10.0%
f 1
10.0%
, 1
10.0%
1
10.0%
U 1
10.0%
. 1
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1
10.0%
c 1
10.0%
h 1
10.0%
a 1
10.0%
r 1
10.0%
f 1
10.0%
, 1
10.0%
1
10.0%
U 1
10.0%
. 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1
10.0%
c 1
10.0%
h 1
10.0%
a 1
10.0%
r 1
10.0%
f 1
10.0%
, 1
10.0%
1
10.0%
U 1
10.0%
. 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1
10.0%
c 1
10.0%
h 1
10.0%
a 1
10.0%
r 1
10.0%
f 1
10.0%
, 1
10.0%
1
10.0%
U 1
10.0%
. 1
10.0%
Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:49.011611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDrosera
2nd rowMiconia
ValueCountFrequency (%)
drosera 1
50.0%
miconia 1
50.0%
2024-12-30T17:03:49.109138image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 2
14.3%
o 2
14.3%
i 2
14.3%
a 2
14.3%
D 1
7.1%
s 1
7.1%
e 1
7.1%
M 1
7.1%
c 1
7.1%
n 1
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 2
14.3%
o 2
14.3%
i 2
14.3%
a 2
14.3%
D 1
7.1%
s 1
7.1%
e 1
7.1%
M 1
7.1%
c 1
7.1%
n 1
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 2
14.3%
o 2
14.3%
i 2
14.3%
a 2
14.3%
D 1
7.1%
s 1
7.1%
e 1
7.1%
M 1
7.1%
c 1
7.1%
n 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 2
14.3%
o 2
14.3%
i 2
14.3%
a 2
14.3%
D 1
7.1%
s 1
7.1%
e 1
7.1%
M 1
7.1%
c 1
7.1%
n 1
7.1%
Distinct3
Distinct (%)100.0%
Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:49.164681image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length7
Mean length13
Min length7

Characters and Unicode

Total characters39
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowDrosera
2nd rowCampanula rotundifolia L.
3rd rowMiconia
ValueCountFrequency (%)
drosera 1
20.0%
campanula 1
20.0%
rotundifolia 1
20.0%
l 1
20.0%
miconia 1
20.0%
2024-12-30T17:03:49.278654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6
15.4%
i 4
 
10.3%
o 4
 
10.3%
r 3
 
7.7%
n 3
 
7.7%
2
 
5.1%
l 2
 
5.1%
u 2
 
5.1%
D 1
 
2.6%
e 1
 
2.6%
Other values (11) 11
28.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 6
15.4%
i 4
 
10.3%
o 4
 
10.3%
r 3
 
7.7%
n 3
 
7.7%
2
 
5.1%
l 2
 
5.1%
u 2
 
5.1%
D 1
 
2.6%
e 1
 
2.6%
Other values (11) 11
28.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 6
15.4%
i 4
 
10.3%
o 4
 
10.3%
r 3
 
7.7%
n 3
 
7.7%
2
 
5.1%
l 2
 
5.1%
u 2
 
5.1%
D 1
 
2.6%
e 1
 
2.6%
Other values (11) 11
28.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 39
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 6
15.4%
i 4
 
10.3%
o 4
 
10.3%
r 3
 
7.7%
n 3
 
7.7%
2
 
5.1%
l 2
 
5.1%
u 2
 
5.1%
D 1
 
2.6%
e 1
 
2.6%
Other values (11) 11
28.2%

group
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

formation
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

member
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:49.329656image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowcoronata
ValueCountFrequency (%)
coronata 1
100.0%
2024-12-30T17:03:49.431342image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2
25.0%
a 2
25.0%
c 1
12.5%
r 1
12.5%
n 1
12.5%
t 1
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2
25.0%
a 2
25.0%
c 1
12.5%
r 1
12.5%
n 1
12.5%
t 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2
25.0%
a 2
25.0%
c 1
12.5%
r 1
12.5%
n 1
12.5%
t 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2
25.0%
a 2
25.0%
c 1
12.5%
r 1
12.5%
n 1
12.5%
t 1
12.5%

bed
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

identificationID
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

verbatimIdentification
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
Distinct24
Distinct (%)0.3%
Missing2352466
Missing (%)99.6%
Memory size18.0 MiB
2024-12-30T17:03:49.484882image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length64
Median length3
Mean length4.292810312
Min length2

Characters and Unicode

Total characters38631
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rownear
2nd rowcf.
3rd rowcf.
4th rowvel aff.
5th rowvel aff.
ValueCountFrequency (%)
cf 6018
65.9%
uncertain 1593
 
17.4%
aff 939
 
10.3%
near 259
 
2.8%
s.l 121
 
1.3%
vel 93
 
1.0%
group 24
 
0.3%
subgroup 23
 
0.3%
sp 21
 
0.2%
nov 15
 
0.2%
Other values (12) 29
 
0.3%
2024-12-30T17:03:49.596955image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 7896
20.4%
c 7622
19.7%
. 7199
18.6%
n 3471
9.0%
a 2802
 
7.3%
e 1963
 
5.1%
r 1904
 
4.9%
u 1624
 
4.2%
t 1602
 
4.1%
i 1598
 
4.1%
Other values (19) 950
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38631
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
f 7896
20.4%
c 7622
19.7%
. 7199
18.6%
n 3471
9.0%
a 2802
 
7.3%
e 1963
 
5.1%
r 1904
 
4.9%
u 1624
 
4.2%
t 1602
 
4.1%
i 1598
 
4.1%
Other values (19) 950
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38631
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
f 7896
20.4%
c 7622
19.7%
. 7199
18.6%
n 3471
9.0%
a 2802
 
7.3%
e 1963
 
5.1%
r 1904
 
4.9%
u 1624
 
4.2%
t 1602
 
4.1%
i 1598
 
4.1%
Other values (19) 950
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38631
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
f 7896
20.4%
c 7622
19.7%
. 7199
18.6%
n 3471
9.0%
a 2802
 
7.3%
e 1963
 
5.1%
r 1904
 
4.9%
u 1624
 
4.2%
t 1602
 
4.1%
i 1598
 
4.1%
Other values (19) 950
 
2.5%

typeStatus
Text

Missing 

Distinct19
Distinct (%)< 0.1%
Missing2274518
Missing (%)96.3%
Memory size18.0 MiB
2024-12-30T17:03:49.657851image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length8
Mean length7.26812886
Min length4

Characters and Unicode

Total characters631942
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowTYPE
2nd rowHOLOTYPE
3rd rowTYPE
4th rowHOLOTYPE
5th rowHOLOTYPE
ValueCountFrequency (%)
holotype 26480
30.5%
paratype 19158
22.0%
isotype 15389
17.7%
type 12139
14.0%
syntype 7658
 
8.8%
lectotype 1798
 
2.1%
isosyntype 1550
 
1.8%
allotype 997
 
1.1%
isolectotype 518
 
0.6%
cotype 484
 
0.6%
Other values (9) 776
 
0.9%
2024-12-30T17:03:49.776345image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 106503
16.9%
Y 96139
15.2%
E 89952
14.2%
T 89665
14.2%
O 75084
11.9%
A 40178
 
6.4%
L 31157
 
4.9%
S 26767
 
4.2%
H 26546
 
4.2%
R 19532
 
3.1%
Other values (10) 30419
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 631942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
P 106503
16.9%
Y 96139
15.2%
E 89952
14.2%
T 89665
14.2%
O 75084
11.9%
A 40178
 
6.4%
L 31157
 
4.9%
S 26767
 
4.2%
H 26546
 
4.2%
R 19532
 
3.1%
Other values (10) 30419
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 631942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
P 106503
16.9%
Y 96139
15.2%
E 89952
14.2%
T 89665
14.2%
O 75084
11.9%
A 40178
 
6.4%
L 31157
 
4.9%
S 26767
 
4.2%
H 26546
 
4.2%
R 19532
 
3.1%
Other values (10) 30419
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 631942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
P 106503
16.9%
Y 96139
15.2%
E 89952
14.2%
T 89665
14.2%
O 75084
11.9%
A 40178
 
6.4%
L 31157
 
4.9%
S 26767
 
4.2%
H 26546
 
4.2%
R 19532
 
3.1%
Other values (10) 30419
 
4.8%

identifiedBy
Text

Missing 

Distinct15491
Distinct (%)3.8%
Missing1955398
Missing (%)82.8%
Memory size18.0 MiB
2024-12-30T17:03:49.939900image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length215
Median length136
Mean length36.86477601
Min length2

Characters and Unicode

Total characters14969569
Distinct characters107
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5875 ?
Unique (%)1.4%

Sample

1st rowBadley, J. E.
2nd rowStrong, M. T., (US), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
3rd rowJohnson, M. W.
4th rowZibrowius, Helmut, (CNRS-UA 41), Centre d'Oceanologie de Marseille (CNRS-UA 41) (FRANCE)
5th rowFoster, W. D.
ValueCountFrequency (%)
of 101962
 
4.6%
museum 88049
 
3.9%
national 87412
 
3.9%
institution 84694
 
3.8%
smithsonian 84068
 
3.8%
natural 83876
 
3.8%
history 83747
 
3.7%
united 76183
 
3.4%
states 75967
 
3.4%
60502
 
2.7%
Other values (11543) 1407833
63.0%
2024-12-30T17:03:50.173390image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1828226
 
12.2%
a 896479
 
6.0%
t 890147
 
5.9%
i 878253
 
5.9%
n 819247
 
5.5%
o 804702
 
5.4%
e 660704
 
4.4%
, 639172
 
4.3%
r 634090
 
4.2%
s 583168
 
3.9%
Other values (97) 6335381
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14969569
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1828226
 
12.2%
a 896479
 
6.0%
t 890147
 
5.9%
i 878253
 
5.9%
n 819247
 
5.5%
o 804702
 
5.4%
e 660704
 
4.4%
, 639172
 
4.3%
r 634090
 
4.2%
s 583168
 
3.9%
Other values (97) 6335381
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14969569
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1828226
 
12.2%
a 896479
 
6.0%
t 890147
 
5.9%
i 878253
 
5.9%
n 819247
 
5.5%
o 804702
 
5.4%
e 660704
 
4.4%
, 639172
 
4.3%
r 634090
 
4.2%
s 583168
 
3.9%
Other values (97) 6335381
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14969569
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1828226
 
12.2%
a 896479
 
6.0%
t 890147
 
5.9%
i 878253
 
5.9%
n 819247
 
5.5%
o 804702
 
5.4%
e 660704
 
4.4%
, 639172
 
4.3%
r 634090
 
4.2%
s 583168
 
3.9%
Other values (97) 6335381
42.3%

identifiedByID
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:50.233346image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length8
Mean length9.666666667
Min length8

Characters and Unicode

Total characters29
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowACCEPTED
2nd rowMagnoliopsida
3rd rowACCEPTED
ValueCountFrequency (%)
accepted 2
66.7%
magnoliopsida 1
33.3%
2024-12-30T17:03:50.338807image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 4
13.8%
E 4
13.8%
A 2
 
6.9%
P 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
a 2
 
6.9%
o 2
 
6.9%
i 2
 
6.9%
M 1
 
3.4%
Other values (6) 6
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 4
13.8%
E 4
13.8%
A 2
 
6.9%
P 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
a 2
 
6.9%
o 2
 
6.9%
i 2
 
6.9%
M 1
 
3.4%
Other values (6) 6
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 4
13.8%
E 4
13.8%
A 2
 
6.9%
P 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
a 2
 
6.9%
o 2
 
6.9%
i 2
 
6.9%
M 1
 
3.4%
Other values (6) 6
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 4
13.8%
E 4
13.8%
A 2
 
6.9%
P 2
 
6.9%
T 2
 
6.9%
D 2
 
6.9%
a 2
 
6.9%
o 2
 
6.9%
i 2
 
6.9%
M 1
 
3.4%
Other values (6) 6
20.7%

dateIdentified
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:50.389858image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsterales
ValueCountFrequency (%)
asterales 1
100.0%
2024-12-30T17:03:50.494047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 2
22.2%
e 2
22.2%
A 1
11.1%
t 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 2
22.2%
e 2
22.2%
A 1
11.1%
t 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 2
22.2%
e 2
22.2%
A 1
11.1%
t 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 2
22.2%
e 2
22.2%
A 1
11.1%
t 1
11.1%
r 1
11.1%
a 1
11.1%
l 1
11.1%

identificationReferences
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:50.560933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowGuatteria punctata (Aubl.) R.A.Howard
ValueCountFrequency (%)
guatteria 1
25.0%
punctata 1
25.0%
aubl 1
25.0%
r.a.howard 1
25.0%
2024-12-30T17:03:50.669592image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5
13.5%
t 4
 
10.8%
u 3
 
8.1%
3
 
8.1%
. 3
 
8.1%
r 2
 
5.4%
A 2
 
5.4%
G 1
 
2.7%
e 1
 
2.7%
p 1
 
2.7%
Other values (12) 12
32.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5
13.5%
t 4
 
10.8%
u 3
 
8.1%
3
 
8.1%
. 3
 
8.1%
r 2
 
5.4%
A 2
 
5.4%
G 1
 
2.7%
e 1
 
2.7%
p 1
 
2.7%
Other values (12) 12
32.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5
13.5%
t 4
 
10.8%
u 3
 
8.1%
3
 
8.1%
. 3
 
8.1%
r 2
 
5.4%
A 2
 
5.4%
G 1
 
2.7%
e 1
 
2.7%
p 1
 
2.7%
Other values (12) 12
32.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5
13.5%
t 4
 
10.8%
u 3
 
8.1%
3
 
8.1%
. 3
 
8.1%
r 2
 
5.4%
A 2
 
5.4%
G 1
 
2.7%
e 1
 
2.7%
p 1
 
2.7%
Other values (12) 12
32.4%
Distinct2
Distinct (%)66.7%
Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:50.741646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length28.33333333
Min length13

Characters and Unicode

Total characters85
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row821cc27a-e3bb-4bc5-ac34-89ada245069d
2nd rowCampanulaceae
3rd row821cc27a-e3bb-4bc5-ac34-89ada245069d
ValueCountFrequency (%)
821cc27a-e3bb-4bc5-ac34-89ada245069d 2
66.7%
campanulaceae 1
33.3%
2024-12-30T17:03:50.860504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12
14.1%
c 9
10.6%
- 8
 
9.4%
2 6
 
7.1%
b 6
 
7.1%
4 6
 
7.1%
3 4
 
4.7%
5 4
 
4.7%
8 4
 
4.7%
e 4
 
4.7%
Other values (12) 22
25.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 85
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12
14.1%
c 9
10.6%
- 8
 
9.4%
2 6
 
7.1%
b 6
 
7.1%
4 6
 
7.1%
3 4
 
4.7%
5 4
 
4.7%
8 4
 
4.7%
e 4
 
4.7%
Other values (12) 22
25.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 85
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12
14.1%
c 9
10.6%
- 8
 
9.4%
2 6
 
7.1%
b 6
 
7.1%
4 6
 
7.1%
3 4
 
4.7%
5 4
 
4.7%
8 4
 
4.7%
e 4
 
4.7%
Other values (12) 22
25.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 85
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12
14.1%
c 9
10.6%
- 8
 
9.4%
2 6
 
7.1%
b 6
 
7.1%
4 6
 
7.1%
3 4
 
4.7%
5 4
 
4.7%
8 4
 
4.7%
e 4
 
4.7%
Other values (12) 22
25.9%

identificationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:50.893504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
ValueCountFrequency (%)
us 2
100.0%
2024-12-30T17:03:50.972941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 2
50.0%
S 2
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 2
50.0%
S 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 2
50.0%
S 2
50.0%

taxonID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:51.039028image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters48
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2024-12-02T13:57:05.005Z
2nd row2024-12-02T13:57:45.829Z
ValueCountFrequency (%)
2024-12-02t13:57:05.005z 1
50.0%
2024-12-02t13:57:45.829z 1
50.0%
2024-12-30T17:03:51.152224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9
18.8%
0 7
14.6%
5 5
10.4%
- 4
8.3%
: 4
8.3%
1 4
8.3%
4 3
 
6.2%
T 2
 
4.2%
3 2
 
4.2%
7 2
 
4.2%
Other values (4) 6
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 48
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 9
18.8%
0 7
14.6%
5 5
10.4%
- 4
8.3%
: 4
8.3%
1 4
8.3%
4 3
 
6.2%
T 2
 
4.2%
3 2
 
4.2%
7 2
 
4.2%
Other values (4) 6
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 48
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 9
18.8%
0 7
14.6%
5 5
10.4%
- 4
8.3%
: 4
8.3%
1 4
8.3%
4 3
 
6.2%
T 2
 
4.2%
3 2
 
4.2%
7 2
 
4.2%
Other values (4) 6
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 48
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 9
18.8%
0 7
14.6%
5 5
10.4%
- 4
8.3%
: 4
8.3%
1 4
8.3%
4 3
 
6.2%
T 2
 
4.2%
3 2
 
4.2%
7 2
 
4.2%
Other values (4) 6
12.5%

scientificNameID
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean69
Minimum69
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:51.200225image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile69
Q169
median69
Q369
95-th percentile69
Maximum69
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean69
Median Absolute Deviation (MAD)0
Skewnessnan
Sum69
Variancenan
MonotonicityStrictly increasing
2024-12-30T17:03:51.244294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
69 1
 
< 0.1%
(Missing) 2361464
> 99.9%
ValueCountFrequency (%)
69 1
< 0.1%
ValueCountFrequency (%)
69 1
< 0.1%

acceptedNameUsageID
Unsupported

Rejected  Unsupported 

Missing5766
Missing (%)0.2%
Memory size18.0 MiB

parentNameUsageID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:51.291298image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowCampanula
ValueCountFrequency (%)
campanula 1
100.0%
2024-12-30T17:03:51.391086image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
33.3%
C 1
 
11.1%
m 1
 
11.1%
p 1
 
11.1%
n 1
 
11.1%
u 1
 
11.1%
l 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3
33.3%
C 1
 
11.1%
m 1
 
11.1%
p 1
 
11.1%
n 1
 
11.1%
u 1
 
11.1%
l 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3
33.3%
C 1
 
11.1%
m 1
 
11.1%
p 1
 
11.1%
n 1
 
11.1%
u 1
 
11.1%
l 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3
33.3%
C 1
 
11.1%
m 1
 
11.1%
p 1
 
11.1%
n 1
 
11.1%
u 1
 
11.1%
l 1
 
11.1%

originalNameUsageID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:51.451822image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length68
Median length68
Mean length68
Min length68

Characters and Unicode

Total characters68
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPlantae, Dicotyledonae (basal), Magnoliales, Annonaceae, Annonoideae
ValueCountFrequency (%)
plantae 1
16.7%
dicotyledonae 1
16.7%
basal 1
16.7%
magnoliales 1
16.7%
annonaceae 1
16.7%
annonoideae 1
16.7%
2024-12-30T17:03:51.568707image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10
14.7%
n 9
13.2%
e 8
11.8%
o 6
8.8%
l 5
 
7.4%
5
 
7.4%
, 4
 
5.9%
i 3
 
4.4%
t 2
 
2.9%
A 2
 
2.9%
Other values (11) 14
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 68
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 10
14.7%
n 9
13.2%
e 8
11.8%
o 6
8.8%
l 5
 
7.4%
5
 
7.4%
, 4
 
5.9%
i 3
 
4.4%
t 2
 
2.9%
A 2
 
2.9%
Other values (11) 14
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 68
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 10
14.7%
n 9
13.2%
e 8
11.8%
o 6
8.8%
l 5
 
7.4%
5
 
7.4%
, 4
 
5.9%
i 3
 
4.4%
t 2
 
2.9%
A 2
 
2.9%
Other values (11) 14
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 68
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 10
14.7%
n 9
13.2%
e 8
11.8%
o 6
8.8%
l 5
 
7.4%
5
 
7.4%
, 4
 
5.9%
i 3
 
4.4%
t 2
 
2.9%
A 2
 
2.9%
Other values (11) 14
20.6%

nameAccordingToID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:51.621701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPlantae
ValueCountFrequency (%)
plantae 1
100.0%
2024-12-30T17:03:51.817232image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2
28.6%
P 1
14.3%
l 1
14.3%
n 1
14.3%
t 1
14.3%
e 1
14.3%

namePublishedInID
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing2361461
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:51.919374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length100
Median length74
Mean length43
Min length12

Characters and Unicode

Total characters172
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;GEODETIC_DATUM_INVALID
2nd rowrotundifolia
3rd rowTracheophyta
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;geodetic_datum_invalid 1
25.0%
rotundifolia 1
25.0%
tracheophyta 1
25.0%
occurrence_status_inferred_from_individual_count 1
25.0%
2024-12-30T17:03:52.067104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 15
 
8.7%
E 13
 
7.6%
D 12
 
7.0%
I 12
 
7.0%
T 11
 
6.4%
U 11
 
6.4%
C 10
 
5.8%
R 10
 
5.8%
N 9
 
5.2%
O 8
 
4.7%
Other values (26) 61
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 172
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 15
 
8.7%
E 13
 
7.6%
D 12
 
7.0%
I 12
 
7.0%
T 11
 
6.4%
U 11
 
6.4%
C 10
 
5.8%
R 10
 
5.8%
N 9
 
5.2%
O 8
 
4.7%
Other values (26) 61
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 172
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 15
 
8.7%
E 13
 
7.6%
D 12
 
7.0%
I 12
 
7.0%
T 11
 
6.4%
U 11
 
6.4%
C 10
 
5.8%
R 10
 
5.8%
N 9
 
5.2%
O 8
 
4.7%
Other values (26) 61
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 172
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 15
 
8.7%
E 13
 
7.6%
D 12
 
7.0%
I 12
 
7.0%
T 11
 
6.4%
U 11
 
6.4%
C 10
 
5.8%
R 10
 
5.8%
N 9
 
5.2%
O 8
 
4.7%
Other values (26) 61
35.5%

taxonConceptID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:52.126760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length11.5
Mean length11.5
Min length10

Characters and Unicode

Total characters23
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowMagnoliopsida
2nd rowStillImage
ValueCountFrequency (%)
magnoliopsida 1
50.0%
stillimage 1
50.0%
2024-12-30T17:03:52.235980image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
13.0%
l 3
13.0%
i 3
13.0%
o 2
 
8.7%
g 2
 
8.7%
M 1
 
4.3%
n 1
 
4.3%
p 1
 
4.3%
s 1
 
4.3%
d 1
 
4.3%
Other values (5) 5
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3
13.0%
l 3
13.0%
i 3
13.0%
o 2
 
8.7%
g 2
 
8.7%
M 1
 
4.3%
n 1
 
4.3%
p 1
 
4.3%
s 1
 
4.3%
d 1
 
4.3%
Other values (5) 5
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3
13.0%
l 3
13.0%
i 3
13.0%
o 2
 
8.7%
g 2
 
8.7%
M 1
 
4.3%
n 1
 
4.3%
p 1
 
4.3%
s 1
 
4.3%
d 1
 
4.3%
Other values (5) 5
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3
13.0%
l 3
13.0%
i 3
13.0%
o 2
 
8.7%
g 2
 
8.7%
M 1
 
4.3%
n 1
 
4.3%
p 1
 
4.3%
s 1
 
4.3%
d 1
 
4.3%
Other values (5) 5
21.7%
Distinct362008
Distinct (%)15.3%
Missing2
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:52.448130image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length234
Median length109
Mean length31.78332034
Min length4

Characters and Unicode

Total characters75055135
Distinct characters128
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179316 ?
Unique (%)7.6%

Sample

1st rowHippolytidae
2nd rowLesquerella lescurii (A.Gray) S.Watson
3rd rowDesmognathus ochrophaeus Cope, 1859
4th rowScleractinia
5th rowNinoe kinbergi Ehlers, 1887
ValueCountFrequency (%)
238208
 
2.6%
l 180173
 
2.0%
ex 82914
 
0.9%
linnaeus 79974
 
0.9%
1758 62066
 
0.7%
var 50926
 
0.6%
plethodon 42963
 
0.5%
1818 33176
 
0.4%
kunth 29864
 
0.3%
dc 29734
 
0.3%
Other values (185831) 8293415
90.9%
2024-12-30T17:03:52.735894image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6761950
 
9.0%
a 6242590
 
8.3%
i 5013451
 
6.7%
e 4703897
 
6.3%
r 3970577
 
5.3%
s 3847327
 
5.1%
o 3620560
 
4.8%
n 3486756
 
4.6%
l 3394828
 
4.5%
u 2955157
 
3.9%
Other values (118) 31058042
41.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 75055135
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6761950
 
9.0%
a 6242590
 
8.3%
i 5013451
 
6.7%
e 4703897
 
6.3%
r 3970577
 
5.3%
s 3847327
 
5.1%
o 3620560
 
4.8%
n 3486756
 
4.6%
l 3394828
 
4.5%
u 2955157
 
3.9%
Other values (118) 31058042
41.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 75055135
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6761950
 
9.0%
a 6242590
 
8.3%
i 5013451
 
6.7%
e 4703897
 
6.3%
r 3970577
 
5.3%
s 3847327
 
5.1%
o 3620560
 
4.8%
n 3486756
 
4.6%
l 3394828
 
4.5%
u 2955157
 
3.9%
Other values (118) 31058042
41.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 75055135
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6761950
 
9.0%
a 6242590
 
8.3%
i 5013451
 
6.7%
e 4703897
 
6.3%
r 3970577
 
5.3%
s 3847327
 
5.1%
o 3620560
 
4.8%
n 3486756
 
4.6%
l 3394828
 
4.5%
u 2955157
 
3.9%
Other values (118) 31058042
41.4%

acceptedNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB

parentNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB

originalNameUsage
Real number (ℝ)

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean3529876
Minimum3190721
Maximum3869031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:52.793292image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum3190721
5-th percentile3224636.5
Q13360298.5
median3529876
Q33699453.5
95-th percentile3835115.5
Maximum3869031
Range678310
Interquartile range (IQR)339155

Descriptive statistics

Standard deviation479637.6007
Coefficient of variation (CV)0.1358794475
Kurtosisnan
Mean3529876
Median Absolute Deviation (MAD)339155
Skewnessnan
Sum7059752
Variance2.30052228 × 1011
MonotonicityStrictly increasing
2024-12-30T17:03:52.842474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
3190721 1
 
< 0.1%
3869031 1
 
< 0.1%
(Missing) 2361463
> 99.9%
ValueCountFrequency (%)
3190721 1
< 0.1%
3869031 1
< 0.1%
ValueCountFrequency (%)
3869031 1
< 0.1%
3190721 1
< 0.1%

nameAccordingTo
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing2361463
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean6
Minimum6
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:52.886826image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q16
median6
Q36
95-th percentile6
Maximum6
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean6
Median Absolute Deviation (MAD)0
Skewnessnan
Sum12
Variance0
MonotonicityIncreasing
2024-12-30T17:03:52.929827image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
6 2
 
< 0.1%
(Missing) 2361463
> 99.9%
ValueCountFrequency (%)
6 2
< 0.1%
ValueCountFrequency (%)
6 2
< 0.1%

namePublishedIn
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB

namePublishedInYear
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
Distinct9381
Distinct (%)0.4%
Missing4992
Missing (%)0.2%
Memory size18.0 MiB
2024-12-30T17:03:53.043211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length164
Median length148
Mean length65.02881001
Min length3

Characters and Unicode

Total characters153238635
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1505 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Arthropoda, Crustacea, Malacostraca, Eumalacostraca, Eucarida, Decapoda, Pleocyemata, Hippolytidae
2nd rowPlantae, Dicotyledonae, Brassicales, Brassicaceae, Brassicoideae
3rd rowAnimalia, Chordata, Vertebrata, Amphibia, Caudata, Plethodontidae
4th rowAnimalia, Cnidaria, Anthozoa, Hexacorallia, Scleractinia
5th rowAnimalia, Annelida, Polychaeta, Errantia, Eunicida, Lumbrineridae
ValueCountFrequency (%)
animalia 1209335
 
9.1%
plantae 1054356
 
7.9%
dicotyledonae 657170
 
4.9%
chordata 572776
 
4.3%
vertebrata 567549
 
4.3%
arthropoda 251879
 
1.9%
monocotyledonae 231105
 
1.7%
mollusca 220773
 
1.7%
poales 178488
 
1.3%
gastropoda 155944
 
1.2%
Other values (9606) 8232767
61.8%
2024-12-30T17:03:53.247247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21342566
13.9%
e 15326706
 
10.0%
i 11163562
 
7.3%
10975669
 
7.2%
, 10942165
 
7.1%
o 9722855
 
6.3%
t 8276865
 
5.4%
l 7536114
 
4.9%
r 7095165
 
4.6%
n 6565956
 
4.3%
Other values (62) 44291012
28.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 153238635
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 21342566
13.9%
e 15326706
 
10.0%
i 11163562
 
7.3%
10975669
 
7.2%
, 10942165
 
7.1%
o 9722855
 
6.3%
t 8276865
 
5.4%
l 7536114
 
4.9%
r 7095165
 
4.6%
n 6565956
 
4.3%
Other values (62) 44291012
28.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 153238635
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 21342566
13.9%
e 15326706
 
10.0%
i 11163562
 
7.3%
10975669
 
7.2%
, 10942165
 
7.1%
o 9722855
 
6.3%
t 8276865
 
5.4%
l 7536114
 
4.9%
r 7095165
 
4.6%
n 6565956
 
4.3%
Other values (62) 44291012
28.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 153238635
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 21342566
13.9%
e 15326706
 
10.0%
i 11163562
 
7.3%
10975669
 
7.2%
, 10942165
 
7.1%
o 9722855
 
6.3%
t 8276865
 
5.4%
l 7536114
 
4.9%
r 7095165
 
4.6%
n 6565956
 
4.3%
Other values (62) 44291012
28.9%
Distinct10
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:53.308242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length8
Mean length7.504671892
Min length4

Characters and Unicode

Total characters17722005
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia
2nd rowPlantae
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 1209386
51.1%
plantae 1054744
44.6%
fungi 56807
 
2.4%
chromista 20874
 
0.9%
bacteria 13612
 
0.6%
incertae 5762
 
0.2%
sedis 5762
 
0.2%
protozoa 275
 
< 0.1%
5399 1
 
< 0.1%
821cc27a-e3bb-4bc5-ac34-89ada245069d 1
 
< 0.1%
2024-12-30T17:03:53.417267image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4582399
25.9%
i 2521589
14.2%
n 2326699
13.1%
l 2264130
12.8%
m 1230260
 
6.9%
A 1209386
 
6.8%
t 1095267
 
6.2%
e 1085643
 
6.1%
P 1055019
 
6.0%
F 56807
 
0.3%
Other values (24) 294806
 
1.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17722005
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4582399
25.9%
i 2521589
14.2%
n 2326699
13.1%
l 2264130
12.8%
m 1230260
 
6.9%
A 1209386
 
6.8%
t 1095267
 
6.2%
e 1085643
 
6.1%
P 1055019
 
6.0%
F 56807
 
0.3%
Other values (24) 294806
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17722005
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4582399
25.9%
i 2521589
14.2%
n 2326699
13.1%
l 2264130
12.8%
m 1230260
 
6.9%
A 1209386
 
6.8%
t 1095267
 
6.2%
e 1085643
 
6.1%
P 1055019
 
6.0%
F 56807
 
0.3%
Other values (24) 294806
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17722005
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4582399
25.9%
i 2521589
14.2%
n 2326699
13.1%
l 2264130
12.8%
m 1230260
 
6.9%
A 1209386
 
6.8%
t 1095267
 
6.2%
e 1085643
 
6.1%
P 1055019
 
6.0%
F 56807
 
0.3%
Other values (24) 294806
 
1.7%

phylum
Text

Distinct64
Distinct (%)< 0.1%
Missing7888
Missing (%)0.3%
Memory size18.0 MiB
2024-12-30T17:03:53.486196image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.11762054
Min length2

Characters and Unicode

Total characters23812599
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowArthropoda
2nd rowTracheophyta
3rd rowChordata
4th rowCnidaria
5th rowAnnelida
ValueCountFrequency (%)
tracheophyta 965311
41.0%
chordata 572771
24.3%
arthropoda 252406
 
10.7%
mollusca 220179
 
9.4%
annelida 61416
 
2.6%
ascomycota 56083
 
2.4%
bryophyta 37922
 
1.6%
rhodophyta 30954
 
1.3%
cnidaria 29998
 
1.3%
echinodermata 23220
 
1.0%
Other values (54) 103317
 
4.4%
2024-12-30T17:03:53.616594image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4009610
16.8%
h 2984383
12.5%
o 2602587
10.9%
r 2209125
9.3%
t 2042901
8.6%
c 1367427
 
5.7%
p 1328235
 
5.6%
y 1197926
 
5.0%
e 1120639
 
4.7%
d 989852
 
4.2%
Other values (37) 3959914
16.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23812599
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4009610
16.8%
h 2984383
12.5%
o 2602587
10.9%
r 2209125
9.3%
t 2042901
8.6%
c 1367427
 
5.7%
p 1328235
 
5.6%
y 1197926
 
5.0%
e 1120639
 
4.7%
d 989852
 
4.2%
Other values (37) 3959914
16.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23812599
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4009610
16.8%
h 2984383
12.5%
o 2602587
10.9%
r 2209125
9.3%
t 2042901
8.6%
c 1367427
 
5.7%
p 1328235
 
5.6%
y 1197926
 
5.0%
e 1120639
 
4.7%
d 989852
 
4.2%
Other values (37) 3959914
16.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23812599
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4009610
16.8%
h 2984383
12.5%
o 2602587
10.9%
r 2209125
9.3%
t 2042901
8.6%
c 1367427
 
5.7%
p 1328235
 
5.6%
y 1197926
 
5.0%
e 1120639
 
4.7%
d 989852
 
4.2%
Other values (37) 3959914
16.6%

class
Text

Missing 

Distinct186
Distinct (%)< 0.1%
Missing138555
Missing (%)5.9%
Memory size18.0 MiB
2024-12-30T17:03:53.752464image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length20
Mean length10.43315114
Min length4

Characters and Unicode

Total characters23191956
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowMalacostraca
2nd rowMagnoliopsida
3rd rowAmphibia
4th rowAnthozoa
5th rowPolychaeta
ValueCountFrequency (%)
magnoliopsida 657370
29.6%
liliopsida 231154
 
10.4%
gastropoda 155259
 
7.0%
mammalia 152953
 
6.9%
insecta 149742
 
6.7%
aves 149231
 
6.7%
amphibia 100689
 
4.5%
malacostraca 76525
 
3.4%
polypodiopsida 63916
 
2.9%
polychaeta 53619
 
2.4%
Other values (176) 432452
19.5%
2024-12-30T17:03:53.967751image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3739588
16.1%
i 2845281
12.3%
o 2681344
11.6%
s 1638014
 
7.1%
p 1464517
 
6.3%
l 1407397
 
6.1%
d 1364592
 
5.9%
n 963712
 
4.2%
M 891567
 
3.8%
e 817658
 
3.5%
Other values (49) 5378286
23.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23191956
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3739588
16.1%
i 2845281
12.3%
o 2681344
11.6%
s 1638014
 
7.1%
p 1464517
 
6.3%
l 1407397
 
6.1%
d 1364592
 
5.9%
n 963712
 
4.2%
M 891567
 
3.8%
e 817658
 
3.5%
Other values (49) 5378286
23.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23191956
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3739588
16.1%
i 2845281
12.3%
o 2681344
11.6%
s 1638014
 
7.1%
p 1464517
 
6.3%
l 1407397
 
6.1%
d 1364592
 
5.9%
n 963712
 
4.2%
M 891567
 
3.8%
e 817658
 
3.5%
Other values (49) 5378286
23.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23191956
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3739588
16.1%
i 2845281
12.3%
o 2681344
11.6%
s 1638014
 
7.1%
p 1464517
 
6.3%
l 1407397
 
6.1%
d 1364592
 
5.9%
n 963712
 
4.2%
M 891567
 
3.8%
e 817658
 
3.5%
Other values (49) 5378286
23.2%

order
Text

Missing 

Distinct926
Distinct (%)< 0.1%
Missing145721
Missing (%)6.2%
Memory size18.0 MiB
2024-12-30T17:03:54.093949image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length9.927911798
Min length5

Characters and Unicode

Total characters21997711
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)< 0.1%

Sample

1st rowDecapoda
2nd rowBrassicales
3rd rowCaudata
4th rowScleractinia
5th rowEunicida
ValueCountFrequency (%)
poales 178531
 
8.1%
asterales 96944
 
4.4%
passeriformes 94751
 
4.3%
rodentia 75757
 
3.4%
lamiales 67866
 
3.1%
fabales 64632
 
2.9%
caudata 60565
 
2.7%
perciformes 54527
 
2.5%
malpighiales 53482
 
2.4%
decapoda 49962
 
2.3%
Other values (916) 1418727
64.0%
2024-12-30T17:03:54.283919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3200606
14.5%
e 2456217
11.2%
s 1919697
 
8.7%
l 1767329
 
8.0%
o 1673369
 
7.6%
i 1557251
 
7.1%
r 1440556
 
6.5%
t 919616
 
4.2%
p 728104
 
3.3%
n 715516
 
3.3%
Other values (46) 5619450
25.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21997711
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3200606
14.5%
e 2456217
11.2%
s 1919697
 
8.7%
l 1767329
 
8.0%
o 1673369
 
7.6%
i 1557251
 
7.1%
r 1440556
 
6.5%
t 919616
 
4.2%
p 728104
 
3.3%
n 715516
 
3.3%
Other values (46) 5619450
25.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21997711
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3200606
14.5%
e 2456217
11.2%
s 1919697
 
8.7%
l 1767329
 
8.0%
o 1673369
 
7.6%
i 1557251
 
7.1%
r 1440556
 
6.5%
t 919616
 
4.2%
p 728104
 
3.3%
n 715516
 
3.3%
Other values (46) 5619450
25.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21997711
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3200606
14.5%
e 2456217
11.2%
s 1919697
 
8.7%
l 1767329
 
8.0%
o 1673369
 
7.6%
i 1557251
 
7.1%
r 1440556
 
6.5%
t 919616
 
4.2%
p 728104
 
3.3%
n 715516
 
3.3%
Other values (46) 5619450
25.5%

superfamily
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:54.346376image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters16
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowMiconia coronata
ValueCountFrequency (%)
miconia 1
50.0%
coronata 1
50.0%
2024-12-30T17:03:54.446884image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3
18.8%
a 3
18.8%
n 2
12.5%
c 2
12.5%
i 2
12.5%
M 1
 
6.2%
1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 3
18.8%
a 3
18.8%
n 2
12.5%
c 2
12.5%
i 2
12.5%
M 1
 
6.2%
1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 3
18.8%
a 3
18.8%
n 2
12.5%
c 2
12.5%
i 2
12.5%
M 1
 
6.2%
1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 3
18.8%
a 3
18.8%
n 2
12.5%
c 2
12.5%
i 2
12.5%
M 1
 
6.2%
1
 
6.2%
r 1
 
6.2%
t 1
 
6.2%

family
Text

Missing 

Distinct6622
Distinct (%)0.3%
Missing52489
Missing (%)2.2%
Memory size18.0 MiB
2024-12-30T17:03:54.540892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length21
Mean length10.85806089
Min length6

Characters and Unicode

Total characters25071002
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique722 ?
Unique (%)< 0.1%

Sample

1st rowHippolytidae
2nd rowBrassicaceae
3rd rowPlethodontidae
4th rowLumbrineridae
5th rowGomphidae
ValueCountFrequency (%)
poaceae 128004
 
5.5%
asteraceae 91253
 
4.0%
fabaceae 60425
 
2.6%
plethodontidae 56509
 
2.4%
cyperaceae 35190
 
1.5%
rubiaceae 30478
 
1.3%
cricetidae 27411
 
1.2%
muridae 23714
 
1.0%
apidae 20894
 
0.9%
melastomataceae 18664
 
0.8%
Other values (6616) 1816438
78.7%
2024-12-30T17:03:54.701920image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4499005
17.9%
e 4442765
17.7%
i 2325126
9.3%
c 1720240
 
6.9%
d 1491888
 
6.0%
o 1265964
 
5.0%
r 1175408
 
4.7%
l 1016477
 
4.1%
t 859959
 
3.4%
n 822238
 
3.3%
Other values (47) 5451932
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25071002
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4499005
17.9%
e 4442765
17.7%
i 2325126
9.3%
c 1720240
 
6.9%
d 1491888
 
6.0%
o 1265964
 
5.0%
r 1175408
 
4.7%
l 1016477
 
4.1%
t 859959
 
3.4%
n 822238
 
3.3%
Other values (47) 5451932
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25071002
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4499005
17.9%
e 4442765
17.7%
i 2325126
9.3%
c 1720240
 
6.9%
d 1491888
 
6.0%
o 1265964
 
5.0%
r 1175408
 
4.7%
l 1016477
 
4.1%
t 859959
 
3.4%
n 822238
 
3.3%
Other values (47) 5451932
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25071002
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4499005
17.9%
e 4442765
17.7%
i 2325126
9.3%
c 1720240
 
6.9%
d 1491888
 
6.0%
o 1265964
 
5.0%
r 1175408
 
4.7%
l 1016477
 
4.1%
t 859959
 
3.4%
n 822238
 
3.3%
Other values (47) 5451932
21.7%

subfamily
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:54.765083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length13.5
Mean length13.5
Min length11

Characters and Unicode

Total characters27
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDrosera sp.
2nd rowMiconia coronata
ValueCountFrequency (%)
drosera 1
25.0%
sp 1
25.0%
miconia 1
25.0%
coronata 1
25.0%
2024-12-30T17:03:54.874294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
14.8%
o 4
14.8%
r 3
11.1%
s 2
7.4%
n 2
7.4%
2
7.4%
c 2
7.4%
i 2
7.4%
e 1
 
3.7%
D 1
 
3.7%
Other values (4) 4
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4
14.8%
o 4
14.8%
r 3
11.1%
s 2
7.4%
n 2
7.4%
2
7.4%
c 2
7.4%
i 2
7.4%
e 1
 
3.7%
D 1
 
3.7%
Other values (4) 4
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4
14.8%
o 4
14.8%
r 3
11.1%
s 2
7.4%
n 2
7.4%
2
7.4%
c 2
7.4%
i 2
7.4%
e 1
 
3.7%
D 1
 
3.7%
Other values (4) 4
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4
14.8%
o 4
14.8%
r 3
11.1%
s 2
7.4%
n 2
7.4%
2
7.4%
c 2
7.4%
i 2
7.4%
e 1
 
3.7%
D 1
 
3.7%
Other values (4) 4
14.8%

tribe
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

subtribe
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:54.943623image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length77
Median length3
Mean length27.66666667
Min length3

Characters and Unicode

Total characters83
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowEML
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84
3rd rowEML
ValueCountFrequency (%)
eml 2
66.7%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 1
33.3%
2024-12-30T17:03:55.070809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 9
 
10.8%
_ 8
 
9.6%
U 6
 
7.2%
D 6
 
7.2%
M 5
 
6.0%
I 5
 
6.0%
T 5
 
6.0%
C 5
 
6.0%
R 5
 
6.0%
S 5
 
6.0%
Other values (11) 24
28.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 83
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 9
 
10.8%
_ 8
 
9.6%
U 6
 
7.2%
D 6
 
7.2%
M 5
 
6.0%
I 5
 
6.0%
T 5
 
6.0%
C 5
 
6.0%
R 5
 
6.0%
S 5
 
6.0%
Other values (11) 24
28.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 83
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 9
 
10.8%
_ 8
 
9.6%
U 6
 
7.2%
D 6
 
7.2%
M 5
 
6.0%
I 5
 
6.0%
T 5
 
6.0%
C 5
 
6.0%
R 5
 
6.0%
S 5
 
6.0%
Other values (11) 24
28.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 83
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 9
 
10.8%
_ 8
 
9.6%
U 6
 
7.2%
D 6
 
7.2%
M 5
 
6.0%
I 5
 
6.0%
T 5
 
6.0%
C 5
 
6.0%
R 5
 
6.0%
S 5
 
6.0%
Other values (11) 24
28.9%

genus
Text

Missing 

Distinct58510
Distinct (%)2.6%
Missing120644
Missing (%)5.1%
Memory size18.0 MiB
2024-12-30T17:03:55.207968image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.034970665
Min length2

Characters and Unicode

Total characters20245752
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16466 ?
Unique (%)0.7%

Sample

1st rowPaysonia
2nd rowDesmognathus
3rd rowNinoe
4th rowHylogomphus
5th rowSkrjabinoclava
ValueCountFrequency (%)
plethodon 42953
 
1.9%
bombus 15824
 
0.7%
carex 14686
 
0.7%
miconia 10093
 
0.5%
peromyscus 10025
 
0.4%
desmognathus 9258
 
0.4%
cladonia 7917
 
0.4%
poa 7658
 
0.3%
cyperus 7007
 
0.3%
paspalum 6575
 
0.3%
Other values (58499) 2108825
94.1%
2024-12-30T17:03:55.406208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2232664
 
11.0%
i 1675014
 
8.3%
o 1648843
 
8.1%
e 1402186
 
6.9%
s 1326799
 
6.6%
r 1282975
 
6.3%
l 1123780
 
5.6%
u 1022138
 
5.0%
n 994213
 
4.9%
t 952492
 
4.7%
Other values (54) 6584648
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20245752
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2232664
 
11.0%
i 1675014
 
8.3%
o 1648843
 
8.1%
e 1402186
 
6.9%
s 1326799
 
6.6%
r 1282975
 
6.3%
l 1123780
 
5.6%
u 1022138
 
5.0%
n 994213
 
4.9%
t 952492
 
4.7%
Other values (54) 6584648
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20245752
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2232664
 
11.0%
i 1675014
 
8.3%
o 1648843
 
8.1%
e 1402186
 
6.9%
s 1326799
 
6.6%
r 1282975
 
6.3%
l 1123780
 
5.6%
u 1022138
 
5.0%
n 994213
 
4.9%
t 952492
 
4.7%
Other values (54) 6584648
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20245752
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2232664
 
11.0%
i 1675014
 
8.3%
o 1648843
 
8.1%
e 1402186
 
6.9%
s 1326799
 
6.6%
r 1282975
 
6.3%
l 1123780
 
5.6%
u 1022138
 
5.0%
n 994213
 
4.9%
t 952492
 
4.7%
Other values (54) 6584648
32.5%

genericName
Text

Missing 

Distinct60030
Distinct (%)2.7%
Missing120736
Missing (%)5.1%
Memory size18.0 MiB
2024-12-30T17:03:55.556235image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.952587305
Min length1

Characters and Unicode

Total characters20060322
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18597 ?
Unique (%)0.8%

Sample

1st rowLesquerella
2nd rowDesmognathus
3rd rowNinoe
4th rowGomphus
5th rowSkrjabinoclava
ValueCountFrequency (%)
plethodon 42953
 
1.9%
bombus 15821
 
0.7%
carex 14678
 
0.7%
peromyscus 10025
 
0.4%
desmognathus 9258
 
0.4%
poa 7661
 
0.3%
cyperus 6995
 
0.3%
cladonia 6779
 
0.3%
paspalum 6559
 
0.3%
solanum 6347
 
0.3%
Other values (60018) 2113653
94.3%
2024-12-30T17:03:55.839689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2206601
 
11.0%
i 1657023
 
8.3%
o 1617618
 
8.1%
e 1383722
 
6.9%
s 1315599
 
6.6%
r 1283426
 
6.4%
l 1102710
 
5.5%
u 1023714
 
5.1%
n 983409
 
4.9%
t 942000
 
4.7%
Other values (55) 6544500
32.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20060322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2206601
 
11.0%
i 1657023
 
8.3%
o 1617618
 
8.1%
e 1383722
 
6.9%
s 1315599
 
6.6%
r 1283426
 
6.4%
l 1102710
 
5.5%
u 1023714
 
5.1%
n 983409
 
4.9%
t 942000
 
4.7%
Other values (55) 6544500
32.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20060322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2206601
 
11.0%
i 1657023
 
8.3%
o 1617618
 
8.1%
e 1383722
 
6.9%
s 1315599
 
6.6%
r 1283426
 
6.4%
l 1102710
 
5.5%
u 1023714
 
5.1%
n 983409
 
4.9%
t 942000
 
4.7%
Other values (55) 6544500
32.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20060322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2206601
 
11.0%
i 1657023
 
8.3%
o 1617618
 
8.1%
e 1383722
 
6.9%
s 1315599
 
6.6%
r 1283426
 
6.4%
l 1102710
 
5.5%
u 1023714
 
5.1%
n 983409
 
4.9%
t 942000
 
4.7%
Other values (55) 6544500
32.6%

subgenus
Boolean

Missing 

Distinct2
Distinct (%)66.7%
Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
True
 
2
False
 
1
(Missing)
2361462 
ValueCountFrequency (%)
True 2
 
< 0.1%
False 1
 
< 0.1%
(Missing) 2361462
> 99.9%
2024-12-30T17:03:55.901453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

infragenericEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB

specificEpithet
Text

Missing 

Distinct101231
Distinct (%)4.9%
Missing306537
Missing (%)13.0%
Memory size18.0 MiB
2024-12-30T17:03:56.041636image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.923929208
Min length2

Characters and Unicode

Total characters18338032
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40686 ?
Unique (%)2.0%

Sample

1st rowlescurii
2nd rowochrophaeus
3rd rowkinbergi
4th rowadelphus
5th rowcouchii
ValueCountFrequency (%)
cinereus 20993
 
1.0%
americana 5520
 
0.3%
gracilis 5231
 
0.3%
canadensis 4690
 
0.2%
maniculatus 4077
 
0.2%
fuscus 4025
 
0.2%
occidentalis 3909
 
0.2%
montanus 3857
 
0.2%
elegans 3772
 
0.2%
carolinensis 3302
 
0.2%
Other values (101221) 1995552
97.1%
2024-12-30T17:03:56.255877image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2365613
12.9%
i 2078357
11.3%
s 1544823
 
8.4%
e 1334633
 
7.3%
r 1236799
 
6.7%
u 1199119
 
6.5%
n 1159867
 
6.3%
l 1147225
 
6.3%
t 1010250
 
5.5%
o 1001337
 
5.5%
Other values (31) 4260009
23.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18338032
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2365613
12.9%
i 2078357
11.3%
s 1544823
 
8.4%
e 1334633
 
7.3%
r 1236799
 
6.7%
u 1199119
 
6.5%
n 1159867
 
6.3%
l 1147225
 
6.3%
t 1010250
 
5.5%
o 1001337
 
5.5%
Other values (31) 4260009
23.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18338032
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2365613
12.9%
i 2078357
11.3%
s 1544823
 
8.4%
e 1334633
 
7.3%
r 1236799
 
6.7%
u 1199119
 
6.5%
n 1159867
 
6.3%
l 1147225
 
6.3%
t 1010250
 
5.5%
o 1001337
 
5.5%
Other values (31) 4260009
23.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18338032
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2365613
12.9%
i 2078357
11.3%
s 1544823
 
8.4%
e 1334633
 
7.3%
r 1236799
 
6.7%
u 1199119
 
6.5%
n 1159867
 
6.3%
l 1147225
 
6.3%
t 1010250
 
5.5%
o 1001337
 
5.5%
Other values (31) 4260009
23.2%

infraspecificEpithet
Text

Missing 

Distinct16294
Distinct (%)7.3%
Missing2138634
Missing (%)90.6%
Memory size18.0 MiB
2024-12-30T17:03:56.374838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length19
Mean length8.952681629
Min length1

Characters and Unicode

Total characters1994935
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5417 ?
Unique (%)2.4%

Sample

1st rowcinnamomina
2nd rowberlandieri
3rd rowmellodora
4th rowrubiginosa
5th rowspergulariiforme
ValueCountFrequency (%)
domesticus 1270
 
0.6%
acuminatum 1170
 
0.5%
pennsylvanicus 1114
 
0.5%
cinereus 977
 
0.4%
talpoides 972
 
0.4%
carolinensis 825
 
0.4%
occidentalis 737
 
0.3%
mexicana 726
 
0.3%
major 669
 
0.3%
borealis 646
 
0.3%
Other values (16284) 213725
95.9%
2024-12-30T17:03:56.549212image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 236092
11.8%
i 231855
11.6%
s 193161
9.7%
e 150019
 
7.5%
n 135896
 
6.8%
r 129914
 
6.5%
u 129816
 
6.5%
l 121955
 
6.1%
o 110496
 
5.5%
c 101725
 
5.1%
Other values (30) 454006
22.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1994935
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 236092
11.8%
i 231855
11.6%
s 193161
9.7%
e 150019
 
7.5%
n 135896
 
6.8%
r 129914
 
6.5%
u 129816
 
6.5%
l 121955
 
6.1%
o 110496
 
5.5%
c 101725
 
5.1%
Other values (30) 454006
22.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1994935
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 236092
11.8%
i 231855
11.6%
s 193161
9.7%
e 150019
 
7.5%
n 135896
 
6.8%
r 129914
 
6.5%
u 129816
 
6.5%
l 121955
 
6.1%
o 110496
 
5.5%
c 101725
 
5.1%
Other values (30) 454006
22.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1994935
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 236092
11.8%
i 231855
11.6%
s 193161
9.7%
e 150019
 
7.5%
n 135896
 
6.8%
r 129914
 
6.5%
u 129816
 
6.5%
l 121955
 
6.1%
o 110496
 
5.5%
c 101725
 
5.1%
Other values (30) 454006
22.8%

cultivarEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
Distinct13
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:56.613708image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length6.997910194
Min length3

Characters and Unicode

Total characters16525306
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowFAMILY
2nd rowSPECIES
3rd rowSPECIES
4th rowORDER
5th rowSPECIES
ValueCountFrequency (%)
species 1832195
77.6%
genus 185798
 
7.9%
subspecies 170097
 
7.2%
family 70045
 
3.0%
variety 50926
 
2.2%
phylum 17766
 
0.8%
class 16815
 
0.7%
order 8393
 
0.4%
kingdom 7620
 
0.3%
form 1804
 
0.1%
Other values (3) 4
 
< 0.1%
2024-12-30T17:03:56.720759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 4394109
26.6%
E 4249704
25.7%
I 2130885
12.9%
P 2020058
12.2%
C 2019109
12.2%
U 373662
 
2.3%
N 193422
 
1.2%
G 193418
 
1.2%
B 170097
 
1.0%
Y 138737
 
0.8%
Other values (14) 642105
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16525306
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 4394109
26.6%
E 4249704
25.7%
I 2130885
12.9%
P 2020058
12.2%
C 2019109
12.2%
U 373662
 
2.3%
N 193422
 
1.2%
G 193418
 
1.2%
B 170097
 
1.0%
Y 138737
 
0.8%
Other values (14) 642105
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16525306
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 4394109
26.6%
E 4249704
25.7%
I 2130885
12.9%
P 2020058
12.2%
C 2019109
12.2%
U 373662
 
2.3%
N 193422
 
1.2%
G 193418
 
1.2%
B 170097
 
1.0%
Y 138737
 
0.8%
Other values (14) 642105
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16525306
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 4394109
26.6%
E 4249704
25.7%
I 2130885
12.9%
P 2020058
12.2%
C 2019109
12.2%
U 373662
 
2.3%
N 193422
 
1.2%
G 193418
 
1.2%
B 170097
 
1.0%
Y 138737
 
0.8%
Other values (14) 642105
 
3.9%

verbatimTaxonRank
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB

vernacularName
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB

nomenclaturalCode
Unsupported

Missing  Rejected  Unsupported 

Missing2361463
Missing (%)> 99.9%
Memory size18.0 MiB
Distinct5
Distinct (%)< 0.1%
Missing5765
Missing (%)0.2%
Memory size18.0 MiB
2024-12-30T17:03:56.778062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length77
Median length8
Mean length7.830019952
Min length7

Characters and Unicode

Total characters18445178
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowACCEPTED
2nd rowSYNONYM
3rd rowACCEPTED
4th rowACCEPTED
5th rowACCEPTED
ValueCountFrequency (%)
accepted 1936163
82.2%
synonym 400501
 
17.0%
doubtful 19034
 
0.8%
northern 1
 
< 0.1%
territory 1
 
< 0.1%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 1
 
< 0.1%
2024-12-30T17:03:56.889518image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 3872333
21.0%
C 3872331
21.0%
T 1955203
10.6%
D 1955203
10.6%
A 1936167
10.5%
P 1936163
10.5%
N 801007
 
4.3%
Y 801002
 
4.3%
O 419539
 
2.3%
S 400506
 
2.2%
Other values (23) 495724
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18445178
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 3872333
21.0%
C 3872331
21.0%
T 1955203
10.6%
D 1955203
10.6%
A 1936167
10.5%
P 1936163
10.5%
N 801007
 
4.3%
Y 801002
 
4.3%
O 419539
 
2.3%
S 400506
 
2.2%
Other values (23) 495724
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18445178
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 3872333
21.0%
C 3872331
21.0%
T 1955203
10.6%
D 1955203
10.6%
A 1936167
10.5%
P 1936163
10.5%
N 801007
 
4.3%
Y 801002
 
4.3%
O 419539
 
2.3%
S 400506
 
2.2%
Other values (23) 495724
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18445178
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 3872333
21.0%
C 3872331
21.0%
T 1955203
10.6%
D 1955203
10.6%
A 1936167
10.5%
P 1936163
10.5%
N 801007
 
4.3%
Y 801002
 
4.3%
O 419539
 
2.3%
S 400506
 
2.2%
Other values (23) 495724
 
2.7%

nomenclaturalStatus
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB

taxonRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing2361462
Missing (%)> 99.9%
Memory size18.0 MiB
Distinct3
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:56.963577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length35.99998221
Min length5

Characters and Unicode

Total characters85012590
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row821cc27a-e3bb-4bc5-ac34-89ada245069d
2nd row821cc27a-e3bb-4bc5-ac34-89ada245069d
3rd row821cc27a-e3bb-4bc5-ac34-89ada245069d
4th row821cc27a-e3bb-4bc5-ac34-89ada245069d
5th row821cc27a-e3bb-4bc5-ac34-89ada245069d
ValueCountFrequency (%)
821cc27a-e3bb-4bc5-ac34-89ada245069d 2361460
> 99.9%
campanula 1
 
< 0.1%
rotundifolia 1
 
< 0.1%
l 1
 
< 0.1%
false 1
 
< 0.1%
2024-12-30T17:03:57.093779image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 9445845
11.1%
c 9445840
11.1%
- 9445840
11.1%
2 7084380
8.3%
4 7084380
8.3%
b 7084380
8.3%
d 4722921
 
5.6%
9 4722920
 
5.6%
5 4722920
 
5.6%
8 4722920
 
5.6%
Other values (21) 16530244
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 85012590
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 9445845
11.1%
c 9445840
11.1%
- 9445840
11.1%
2 7084380
8.3%
4 7084380
8.3%
b 7084380
8.3%
d 4722921
 
5.6%
9 4722920
 
5.6%
5 4722920
 
5.6%
8 4722920
 
5.6%
Other values (21) 16530244
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 85012590
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 9445845
11.1%
c 9445840
11.1%
- 9445840
11.1%
2 7084380
8.3%
4 7084380
8.3%
b 7084380
8.3%
d 4722921
 
5.6%
9 4722920
 
5.6%
5 4722920
 
5.6%
8 4722920
 
5.6%
Other values (21) 16530244
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 85012590
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 9445845
11.1%
c 9445840
11.1%
- 9445840
11.1%
2 7084380
8.3%
4 7084380
8.3%
b 7084380
8.3%
d 4722921
 
5.6%
9 4722920
 
5.6%
5 4722920
 
5.6%
8 4722920
 
5.6%
Other values (21) 16530244
19.4%
Distinct3
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:57.134975image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length2
Mean length2.000010587
Min length2

Characters and Unicode

Total characters4722949
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 2361460
> 99.9%
campanula 1
 
< 0.1%
rotundifolia 1
 
< 0.1%
3155772 1
 
< 0.1%
2024-12-30T17:03:57.237092image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 2361460
50.0%
S 2361460
50.0%
a 4
 
< 0.1%
u 2
 
< 0.1%
n 2
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
l 2
 
< 0.1%
o 2
 
< 0.1%
i 2
 
< 0.1%
Other values (11) 11
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4722949
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 2361460
50.0%
S 2361460
50.0%
a 4
 
< 0.1%
u 2
 
< 0.1%
n 2
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
l 2
 
< 0.1%
o 2
 
< 0.1%
i 2
 
< 0.1%
Other values (11) 11
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4722949
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 2361460
50.0%
S 2361460
50.0%
a 4
 
< 0.1%
u 2
 
< 0.1%
n 2
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
l 2
 
< 0.1%
o 2
 
< 0.1%
i 2
 
< 0.1%
Other values (11) 11
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4722949
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 2361460
50.0%
S 2361460
50.0%
a 4
 
< 0.1%
u 2
 
< 0.1%
n 2
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
l 2
 
< 0.1%
o 2
 
< 0.1%
i 2
 
< 0.1%
Other values (11) 11
 
< 0.1%
Distinct210763
Distinct (%)8.9%
Missing2
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:57.369689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99606473
Min length2

Characters and Unicode

Total characters56665819
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7659 ?
Unique (%)0.3%

Sample

1st row2024-12-02T13:59:36.683Z
2nd row2024-12-02T13:59:14.817Z
3rd row2024-12-02T13:57:42.802Z
4th row2024-12-02T13:59:13.837Z
5th row2024-12-02T13:57:45.358Z
ValueCountFrequency (%)
2024-12-02t13:57:25.039z 46
 
< 0.1%
2024-12-02t13:57:45.003z 45
 
< 0.1%
2024-12-02t13:57:24.083z 45
 
< 0.1%
2024-12-02t13:57:28.833z 45
 
< 0.1%
2024-12-02t13:57:52.915z 44
 
< 0.1%
2024-12-02t13:57:34.491z 44
 
< 0.1%
2024-12-02t13:57:52.924z 43
 
< 0.1%
2024-12-02t13:57:43.166z 43
 
< 0.1%
2024-12-02t13:57:49.759z 42
 
< 0.1%
2024-12-02t13:57:52.893z 42
 
< 0.1%
Other values (210753) 2361024
> 99.9%
2024-12-30T17:03:57.571955image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10789974
19.0%
0 5989862
10.6%
1 5962966
10.5%
: 4722920
8.3%
- 4722920
8.3%
4 3794952
 
6.7%
5 3740549
 
6.6%
3 3738232
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (9) 8480524
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56665819
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 10789974
19.0%
0 5989862
10.6%
1 5962966
10.5%
: 4722920
8.3%
- 4722920
8.3%
4 3794952
 
6.7%
5 3740549
 
6.6%
3 3738232
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (9) 8480524
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56665819
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 10789974
19.0%
0 5989862
10.6%
1 5962966
10.5%
: 4722920
8.3%
- 4722920
8.3%
4 3794952
 
6.7%
5 3740549
 
6.6%
3 3738232
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (9) 8480524
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56665819
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 10789974
19.0%
0 5989862
10.6%
1 5962966
10.5%
: 4722920
8.3%
- 4722920
8.3%
4 3794952
 
6.7%
5 3740549
 
6.6%
3 3738232
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (9) 8480524
15.0%

elevation
Unsupported

Missing  Rejected  Unsupported 

Missing1813932
Missing (%)76.8%
Memory size18.0 MiB

elevationAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing2160161
Missing (%)91.5%
Memory size18.0 MiB

depth
Unsupported

Missing  Rejected  Unsupported 

Missing2098482
Missing (%)88.9%
Memory size18.0 MiB

depthAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing2120412
Missing (%)89.8%
Memory size18.0 MiB

distanceFromCentroidInMeters
Real number (ℝ)

Missing 

Distinct910
Distinct (%)19.6%
Missing2356823
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean2072.410678
Minimum0
Maximum9291
Zeros906
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:57.637612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1365.9456783
median1914.901062
Q33805.441144
95-th percentile4823.124054
Maximum9291
Range9291
Interquartile range (IQR)3439.495466

Descriptive statistics

Standard deviation1702.431563
Coefficient of variation (CV)0.8214740358
Kurtosis-1.351063222
Mean2072.410678
Median Absolute Deviation (MAD)1602.647806
Skewness0.2280801553
Sum9620130.367
Variance2898273.228
MonotonicityNot monotonic
2024-12-30T17:03:57.696686image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 906
 
< 0.1%
511.1528955 224
 
< 0.1%
4105.643933 143
 
< 0.1%
365.9456783 97
 
< 0.1%
2063.191632 87
 
< 0.1%
4961.494347 60
 
< 0.1%
2015.720707 54
 
< 0.1%
1436.265125 53
 
< 0.1%
949.7490617 46
 
< 0.1%
3997.886559 41
 
< 0.1%
Other values (900) 2931
 
0.1%
(Missing) 2356823
99.8%
ValueCountFrequency (%)
0 906
< 0.1%
3.317440985 1
 
< 0.1%
3.591589964 3
 
< 0.1%
3.650579246 26
 
< 0.1%
3.654429861 1
 
< 0.1%
ValueCountFrequency (%)
9291 1
 
< 0.1%
4999.217006 6
< 0.1%
4992.128921 1
 
< 0.1%
4982.251946 1
 
< 0.1%
4980.294784 1
 
< 0.1%

issue
Text

Distinct541
Distinct (%)< 0.1%
Missing852
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:03:57.768216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length210
Median length48
Mean length67.70643642
Min length7

Characters and Unicode

Total characters159828694
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)< 0.1%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES;CONTINENT_INVALID
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
3rd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
5th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT;GEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_INVALID
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count 1322725
56.0%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 251044
 
10.6%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_invalid 152222
 
6.4%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;continent_invalid 105605
 
4.5%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 86812
 
3.7%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_derived_from_coordinates 76729
 
3.3%
occurrence_status_inferred_from_individual_count;taxon_match_higherrank 71534
 
3.0%
occurrence_status_inferred_from_individual_count;continent_derived_from_country 67959
 
2.9%
occurrence_status_inferred_from_individual_count;taxon_match_fuzzy 25595
 
1.1%
occurrence_status_inferred_from_individual_count;recorded_date_mismatch 25313
 
1.1%
Other values (531) 175075
 
7.4%
2024-12-30T17:03:57.914133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 15993110
10.0%
E 13659218
 
8.5%
R 13467823
 
8.4%
N 13134550
 
8.2%
I 12670207
 
7.9%
C 11725720
 
7.3%
U 11078299
 
6.9%
T 11054854
 
6.9%
D 10756285
 
6.7%
O 9975135
 
6.2%
Other values (24) 36313493
22.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 159828694
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 15993110
10.0%
E 13659218
 
8.5%
R 13467823
 
8.4%
N 13134550
 
8.2%
I 12670207
 
7.9%
C 11725720
 
7.3%
U 11078299
 
6.9%
T 11054854
 
6.9%
D 10756285
 
6.7%
O 9975135
 
6.2%
Other values (24) 36313493
22.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 159828694
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 15993110
10.0%
E 13659218
 
8.5%
R 13467823
 
8.4%
N 13134550
 
8.2%
I 12670207
 
7.9%
C 11725720
 
7.3%
U 11078299
 
6.9%
T 11054854
 
6.9%
D 10756285
 
6.7%
O 9975135
 
6.2%
Other values (24) 36313493
22.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 159828694
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 15993110
10.0%
E 13659218
 
8.5%
R 13467823
 
8.4%
N 13134550
 
8.2%
I 12670207
 
7.9%
C 11725720
 
7.3%
U 11078299
 
6.9%
T 11054854
 
6.9%
D 10756285
 
6.7%
O 9975135
 
6.2%
Other values (24) 36313493
22.7%

mediaType
Text

Missing 

Distinct59
Distinct (%)< 0.1%
Missing863240
Missing (%)36.6%
Memory size18.0 MiB
2024-12-30T17:03:57.971133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1011
Median length10
Mean length11.32266182
Min length5

Characters and Unicode

Total characters16963895
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowStillImage
2nd rowStillImage
3rd rowStillImage
4th rowStillImage
5th rowStillImage
ValueCountFrequency (%)
stillimage 1393845
93.0%
stillimage;stillimage 79719
 
5.3%
stillimage;stillimage;stillimage 8722
 
0.6%
stillimage;stillimage;stillimage;stillimage 7143
 
0.5%
stillimage;stillimage;stillimage;stillimage;stillimage 2786
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 2282
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 958
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 570
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 531
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 332
 
< 0.1%
Other values (49) 1337
 
0.1%
2024-12-30T17:03:58.106170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 3356749
19.8%
a 1678375
9.9%
e 1678375
9.9%
S 1678374
9.9%
i 1678374
9.9%
t 1678374
9.9%
m 1678374
9.9%
I 1678374
9.9%
g 1678374
9.9%
; 180150
 
1.1%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16963895
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 3356749
19.8%
a 1678375
9.9%
e 1678375
9.9%
S 1678374
9.9%
i 1678374
9.9%
t 1678374
9.9%
m 1678374
9.9%
I 1678374
9.9%
g 1678374
9.9%
; 180150
 
1.1%
Other values (2) 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16963895
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 3356749
19.8%
a 1678375
9.9%
e 1678375
9.9%
S 1678374
9.9%
i 1678374
9.9%
t 1678374
9.9%
m 1678374
9.9%
I 1678374
9.9%
g 1678374
9.9%
; 180150
 
1.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16963895
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 3356749
19.8%
a 1678375
9.9%
e 1678375
9.9%
S 1678374
9.9%
i 1678374
9.9%
t 1678374
9.9%
m 1678374
9.9%
I 1678374
9.9%
g 1678374
9.9%
; 180150
 
1.1%
Other values (2) 2
 
< 0.1%

hasCoordinate
Unsupported

Rejected  Unsupported 

Missing3
Missing (%)< 0.1%
Memory size18.0 MiB

hasGeospatialIssues
Unsupported

Rejected  Unsupported 

Missing3
Missing (%)< 0.1%
Memory size18.0 MiB

taxonKey
Unsupported

Rejected  Unsupported 

Missing4
Missing (%)< 0.1%
Memory size18.0 MiB

acceptedTaxonKey
Unsupported

Rejected  Unsupported 

Missing5766
Missing (%)0.2%
Memory size18.0 MiB

kingdomKey
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.365774563
Minimum0
Maximum7
Zeros5762
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:58.151192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.462413314
Coefficient of variation (CV)0.7316037565
Kurtosis-1.96490249
Mean3.365774563
Median Absolute Deviation (MAD)0
Skewness0.09395173098
Sum7948142
Variance6.063479329
MonotonicityNot monotonic
2024-12-30T17:03:58.197195image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1209386
51.2%
6 1054744
44.7%
5 56807
 
2.4%
4 20874
 
0.9%
3 13612
 
0.6%
0 5762
 
0.2%
7 275
 
< 0.1%
(Missing) 5
 
< 0.1%
ValueCountFrequency (%)
0 5762
 
0.2%
1 1209386
51.2%
3 13612
 
0.6%
4 20874
 
0.9%
5 56807
 
2.4%
ValueCountFrequency (%)
7 275
 
< 0.1%
6 1054744
44.7%
5 56807
 
2.4%
4 20874
 
0.9%
3 13612
 
0.6%

phylumKey
Unsupported

Rejected  Unsupported 

Missing7890
Missing (%)0.3%
Memory size18.0 MiB

classKey
Unsupported

Missing  Rejected  Unsupported 

Missing138556
Missing (%)5.9%
Memory size18.0 MiB

orderKey
Unsupported

Missing  Rejected  Unsupported 

Missing145721
Missing (%)6.2%
Memory size18.0 MiB

familyKey
Unsupported

Missing  Rejected  Unsupported 

Missing52491
Missing (%)2.2%
Memory size18.0 MiB

genusKey
Real number (ℝ)

Missing 

Distinct59193
Distinct (%)2.6%
Missing120648
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean3456731.817
Minimum1000426
Maximum12386603
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.0 MiB
2024-12-30T17:03:58.254157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1000426
5-th percentile1879915
Q12431477
median2704427
Q33172047
95-th percentile8303739
Maximum12386603
Range11386177
Interquartile range (IQR)740570

Descriptive statistics

Standard deviation2028761.07
Coefficient of variation (CV)0.5869014945
Kurtosis3.425987991
Mean3456731.817
Median Absolute Deviation (MAD)357736
Skewness2.059821455
Sum7.74590342 × 1012
Variance4.115871478 × 1012
MonotonicityNot monotonic
2024-12-30T17:03:58.315156image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2431477 42953
 
1.8%
1340278 15824
 
0.7%
2721893 14686
 
0.6%
3188558 10093
 
0.4%
2437961 10025
 
0.4%
2431198 9258
 
0.4%
2607519 7917
 
0.3%
2704173 7658
 
0.3%
2713455 7007
 
0.3%
2705540 6575
 
0.3%
Other values (59183) 2108821
89.3%
(Missing) 120648
 
5.1%
ValueCountFrequency (%)
1000426 6
< 0.1%
1000456 3
< 0.1%
1000486 1
 
< 0.1%
1000491 4
< 0.1%
1000533 1
 
< 0.1%
ValueCountFrequency (%)
12386603 1
 
< 0.1%
12385823 16
< 0.1%
12379558 2
 
< 0.1%
12375178 5
 
< 0.1%
12373983 1
 
< 0.1%

subgenusKey
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:58.351452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowNE
ValueCountFrequency (%)
ne 1
100.0%
2024-12-30T17:03:58.428452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1
50.0%
E 1
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1
50.0%
E 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1
50.0%
E 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1
50.0%
E 1
50.0%

speciesKey
Unsupported

Missing  Rejected  Unsupported 

Missing306496
Missing (%)13.0%
Memory size18.0 MiB

species
Text

Missing 

Distinct270916
Distinct (%)13.2%
Missing306496
Missing (%)13.0%
Memory size18.0 MiB
2024-12-30T17:03:58.595606image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length41
Median length35
Mean length18.94209548
Min length7

Characters and Unicode

Total characters38925419
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123376 ?
Unique (%)6.0%

Sample

1st rowPaysonia lescurii
2nd rowDesmognathus ochrophaeus
3rd rowNinoe kinbergi
4th rowHylogomphus adelphus
5th rowScaphiopus couchii
ValueCountFrequency (%)
plethodon 42272
 
1.0%
cinereus 21325
 
0.5%
carex 14397
 
0.4%
bombus 13087
 
0.3%
peromyscus 10009
 
0.2%
miconia 9511
 
0.2%
desmognathus 9016
 
0.2%
cladonia 7557
 
0.2%
poa 7484
 
0.2%
cyperus 6932
 
0.2%
Other values (144981) 3968536
96.6%
2024-12-30T17:03:58.841266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4398024
 
11.3%
i 3607850
 
9.3%
s 2760190
 
7.1%
e 2620737
 
6.7%
o 2514893
 
6.5%
r 2406574
 
6.2%
l 2172599
 
5.6%
u 2139863
 
5.5%
n 2075733
 
5.3%
2055157
 
5.3%
Other values (46) 12173799
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38925419
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4398024
 
11.3%
i 3607850
 
9.3%
s 2760190
 
7.1%
e 2620737
 
6.7%
o 2514893
 
6.5%
r 2406574
 
6.2%
l 2172599
 
5.6%
u 2139863
 
5.5%
n 2075733
 
5.3%
2055157
 
5.3%
Other values (46) 12173799
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38925419
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4398024
 
11.3%
i 3607850
 
9.3%
s 2760190
 
7.1%
e 2620737
 
6.7%
o 2514893
 
6.5%
r 2406574
 
6.2%
l 2172599
 
5.6%
u 2139863
 
5.5%
n 2075733
 
5.3%
2055157
 
5.3%
Other values (46) 12173799
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38925419
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4398024
 
11.3%
i 3607850
 
9.3%
s 2760190
 
7.1%
e 2620737
 
6.7%
o 2514893
 
6.5%
r 2406574
 
6.2%
l 2172599
 
5.6%
u 2139863
 
5.5%
n 2075733
 
5.3%
2055157
 
5.3%
Other values (46) 12173799
31.3%
Distinct315017
Distinct (%)13.4%
Missing5766
Missing (%)0.2%
Memory size18.0 MiB
2024-12-30T17:03:59.065755image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length234
Median length129
Mean length32.19436694
Min length4

Characters and Unicode

Total characters75840238
Distinct characters134
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142213 ?
Unique (%)6.0%

Sample

1st rowHippolytidae
2nd rowPaysonia lescurii (A.Gray) O'Kane & Al-Shehbaz
3rd rowDesmognathus ochrophaeus Cope, 1859
4th rowScleractinia
5th rowNinoe kinbergi Ehlers, 1887
ValueCountFrequency (%)
263619
 
2.9%
l 187761
 
2.0%
ex 84339
 
0.9%
linnaeus 82433
 
0.9%
1758 64115
 
0.7%
plethodon 42963
 
0.5%
var 34730
 
0.4%
1818 33708
 
0.4%
subsp 33211
 
0.4%
kunth 31136
 
0.3%
Other values (179003) 8332851
90.7%
2024-12-30T17:03:59.426206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6835167
 
9.0%
a 6257786
 
8.3%
i 5019795
 
6.6%
e 4734753
 
6.2%
r 3964576
 
5.2%
s 3861382
 
5.1%
o 3664221
 
4.8%
n 3503273
 
4.6%
l 3422087
 
4.5%
u 2966099
 
3.9%
Other values (124) 31611099
41.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 75840238
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6835167
 
9.0%
a 6257786
 
8.3%
i 5019795
 
6.6%
e 4734753
 
6.2%
r 3964576
 
5.2%
s 3861382
 
5.1%
o 3664221
 
4.8%
n 3503273
 
4.6%
l 3422087
 
4.5%
u 2966099
 
3.9%
Other values (124) 31611099
41.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 75840238
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6835167
 
9.0%
a 6257786
 
8.3%
i 5019795
 
6.6%
e 4734753
 
6.2%
r 3964576
 
5.2%
s 3861382
 
5.1%
o 3664221
 
4.8%
n 3503273
 
4.6%
l 3422087
 
4.5%
u 2966099
 
3.9%
Other values (124) 31611099
41.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 75840238
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6835167
 
9.0%
a 6257786
 
8.3%
i 5019795
 
6.6%
e 4734753
 
6.2%
r 3964576
 
5.2%
s 3861382
 
5.1%
o 3664221
 
4.8%
n 3503273
 
4.6%
l 3422087
 
4.5%
u 2966099
 
3.9%
Other values (124) 31611099
41.7%
Distinct389004
Distinct (%)17.2%
Missing94299
Missing (%)4.0%
Memory size18.0 MiB
2024-12-30T17:03:59.630083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length125
Median length97
Mean length20.1873352
Min length3

Characters and Unicode

Total characters45768040
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203003 ?
Unique (%)9.0%

Sample

1st rowLesquerella lescurii
2nd rowDesmognathus ochrophaeus
3rd rowNinoe kinbergi
4th rowGomphus adelphus
5th rowSkrjabinoclava catoptrophori
ValueCountFrequency (%)
sp 138550
 
2.8%
var 54090
 
1.1%
plethodon 42963
 
0.9%
subsp 26921
 
0.5%
cinereus 21966
 
0.4%
bombus 17610
 
0.4%
carex 14678
 
0.3%
indet 10551
 
0.2%
peromyscus 10026
 
0.2%
desmognathus 9258
 
0.2%
Other values (177027) 4602652
93.0%
2024-12-30T17:03:59.917363image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5045322
 
11.0%
i 4145957
 
9.1%
s 3377284
 
7.4%
e 3010560
 
6.6%
o 2851323
 
6.2%
r 2816880
 
6.2%
2682099
 
5.9%
u 2473140
 
5.4%
l 2459206
 
5.4%
n 2395932
 
5.2%
Other values (84) 14510337
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45768040
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5045322
 
11.0%
i 4145957
 
9.1%
s 3377284
 
7.4%
e 3010560
 
6.6%
o 2851323
 
6.2%
r 2816880
 
6.2%
2682099
 
5.9%
u 2473140
 
5.4%
l 2459206
 
5.4%
n 2395932
 
5.2%
Other values (84) 14510337
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45768040
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5045322
 
11.0%
i 4145957
 
9.1%
s 3377284
 
7.4%
e 3010560
 
6.6%
o 2851323
 
6.2%
r 2816880
 
6.2%
2682099
 
5.9%
u 2473140
 
5.4%
l 2459206
 
5.4%
n 2395932
 
5.2%
Other values (84) 14510337
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45768040
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5045322
 
11.0%
i 4145957
 
9.1%
s 3377284
 
7.4%
e 3010560
 
6.6%
o 2851323
 
6.2%
r 2816880
 
6.2%
2682099
 
5.9%
u 2473140
 
5.4%
l 2459206
 
5.4%
n 2395932
 
5.2%
Other values (84) 14510337
31.7%

typifiedName
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing2361464
Missing (%)> 99.9%
Memory size18.0 MiB
2024-12-30T17:03:59.977022image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowFrench Guiana
ValueCountFrequency (%)
french 1
50.0%
guiana 1
50.0%
2024-12-30T17:04:00.077749image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2
15.4%
a 2
15.4%
F 1
7.7%
e 1
7.7%
r 1
7.7%
h 1
7.7%
c 1
7.7%
1
7.7%
G 1
7.7%
u 1
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 2
15.4%
a 2
15.4%
F 1
7.7%
e 1
7.7%
r 1
7.7%
h 1
7.7%
c 1
7.7%
1
7.7%
G 1
7.7%
u 1
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 2
15.4%
a 2
15.4%
F 1
7.7%
e 1
7.7%
r 1
7.7%
h 1
7.7%
c 1
7.7%
1
7.7%
G 1
7.7%
u 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 2
15.4%
a 2
15.4%
F 1
7.7%
e 1
7.7%
r 1
7.7%
h 1
7.7%
c 1
7.7%
1
7.7%
G 1
7.7%
u 1
7.7%
Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:04:00.118442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.000001694
Min length3

Characters and Unicode

Total characters7084387
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 2361460
> 99.9%
guf.1_1 1
 
< 0.1%
2024-12-30T17:04:00.218094image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 2361460
33.3%
M 2361460
33.3%
L 2361460
33.3%
1 2
 
< 0.1%
G 1
 
< 0.1%
U 1
 
< 0.1%
F 1
 
< 0.1%
. 1
 
< 0.1%
_ 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7084387
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 2361460
33.3%
M 2361460
33.3%
L 2361460
33.3%
1 2
 
< 0.1%
G 1
 
< 0.1%
U 1
 
< 0.1%
F 1
 
< 0.1%
. 1
 
< 0.1%
_ 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7084387
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 2361460
33.3%
M 2361460
33.3%
L 2361460
33.3%
1 2
 
< 0.1%
G 1
 
< 0.1%
U 1
 
< 0.1%
F 1
 
< 0.1%
. 1
 
< 0.1%
_ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7084387
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 2361460
33.3%
M 2361460
33.3%
L 2361460
33.3%
1 2
 
< 0.1%
G 1
 
< 0.1%
U 1
 
< 0.1%
F 1
 
< 0.1%
. 1
 
< 0.1%
_ 1
 
< 0.1%
Distinct210761
Distinct (%)8.9%
Missing4
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:04:00.350529image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99608336
Min length7

Characters and Unicode

Total characters56665815
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7657 ?
Unique (%)0.3%

Sample

1st row2024-12-02T13:59:36.683Z
2nd row2024-12-02T13:59:14.817Z
3rd row2024-12-02T13:57:42.802Z
4th row2024-12-02T13:59:13.837Z
5th row2024-12-02T13:57:45.358Z
ValueCountFrequency (%)
2024-12-02t13:57:25.039z 46
 
< 0.1%
2024-12-02t13:57:28.833z 45
 
< 0.1%
2024-12-02t13:57:45.003z 45
 
< 0.1%
2024-12-02t13:57:24.083z 45
 
< 0.1%
2024-12-02t13:57:52.915z 44
 
< 0.1%
2024-12-02t13:57:34.491z 44
 
< 0.1%
2024-12-02t13:57:52.924z 43
 
< 0.1%
2024-12-02t13:57:43.166z 43
 
< 0.1%
2024-12-02t13:57:42.743z 42
 
< 0.1%
2024-12-02t13:57:49.759z 42
 
< 0.1%
Other values (210751) 2361022
> 99.9%
2024-12-30T17:04:00.547646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10789973
19.0%
0 5989862
10.6%
1 5962965
10.5%
- 4722920
8.3%
: 4722920
8.3%
4 3794952
 
6.7%
5 3740547
 
6.6%
3 3738231
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (10) 8480525
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56665815
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 10789973
19.0%
0 5989862
10.6%
1 5962965
10.5%
- 4722920
8.3%
: 4722920
8.3%
4 3794952
 
6.7%
5 3740547
 
6.6%
3 3738231
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (10) 8480525
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56665815
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 10789973
19.0%
0 5989862
10.6%
1 5962965
10.5%
- 4722920
8.3%
: 4722920
8.3%
4 3794952
 
6.7%
5 3740547
 
6.6%
3 3738231
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (10) 8480525
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56665815
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 10789973
19.0%
0 5989862
10.6%
1 5962965
10.5%
- 4722920
8.3%
: 4722920
8.3%
4 3794952
 
6.7%
5 3740547
 
6.6%
3 3738231
 
6.6%
T 2361460
 
4.2%
Z 2361460
 
4.2%
Other values (10) 8480525
15.0%
Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:04:00.619090image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99999407
Min length10

Characters and Unicode

Total characters56675050
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-02T11:48:23.416Z
2nd row2024-12-02T11:48:23.416Z
3rd row2024-12-02T11:48:23.416Z
4th row2024-12-02T11:48:23.416Z
5th row2024-12-02T11:48:23.416Z
ValueCountFrequency (%)
2024-12-02t11:48:23.416z 2361460
> 99.9%
guf.1.11_1 1
 
< 0.1%
2024-12-30T17:04:00.733721image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11807300
20.8%
1 9445844
16.7%
4 7084380
12.5%
0 4722920
 
8.3%
- 4722920
 
8.3%
: 4722920
 
8.3%
. 2361462
 
4.2%
T 2361460
 
4.2%
8 2361460
 
4.2%
3 2361460
 
4.2%
Other values (6) 4722924
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56675050
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 11807300
20.8%
1 9445844
16.7%
4 7084380
12.5%
0 4722920
 
8.3%
- 4722920
 
8.3%
: 4722920
 
8.3%
. 2361462
 
4.2%
T 2361460
 
4.2%
8 2361460
 
4.2%
3 2361460
 
4.2%
Other values (6) 4722924
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56675050
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 11807300
20.8%
1 9445844
16.7%
4 7084380
12.5%
0 4722920
 
8.3%
- 4722920
 
8.3%
: 4722920
 
8.3%
. 2361462
 
4.2%
T 2361460
 
4.2%
8 2361460
 
4.2%
3 2361460
 
4.2%
Other values (6) 4722924
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56675050
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 11807300
20.8%
1 9445844
16.7%
4 7084380
12.5%
0 4722920
 
8.3%
- 4722920
 
8.3%
: 4722920
 
8.3%
. 2361462
 
4.2%
T 2361460
 
4.2%
8 2361460
 
4.2%
3 2361460
 
4.2%
Other values (6) 4722924
8.3%

repatriated
Unsupported

Missing  Rejected  Unsupported 

Missing92306
Missing (%)3.9%
Memory size18.0 MiB

relativeOrganismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

projectId
Unsupported

Missing  Rejected  Unsupported 

Missing2361465
Missing (%)100.0%
Memory size18.0 MiB

isSequenced
Unsupported

Rejected  Unsupported 

Missing4
Missing (%)< 0.1%
Memory size18.0 MiB

gbifRegion
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing114367
Missing (%)4.8%
Memory size18.0 MiB
2024-12-30T17:04:00.791985image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.97984334
Min length4

Characters and Unicode

Total characters24672784
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLATIN_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 899421
40.0%
latin_america 745190
33.2%
asia 257467
 
11.5%
oceania 127573
 
5.7%
africa 108539
 
4.8%
europe 92588
 
4.1%
antarctica 16320
 
0.7%
2024-12-30T17:04:00.904046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 5070530
20.6%
I 2899700
11.8%
R 2761479
11.2%
E 1957360
 
7.9%
C 1913363
 
7.8%
N 1788504
 
7.2%
T 1677251
 
6.8%
M 1644611
 
6.7%
_ 1644611
 
6.7%
O 1119582
 
4.5%
Other values (6) 2195793
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24672784
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 5070530
20.6%
I 2899700
11.8%
R 2761479
11.2%
E 1957360
 
7.9%
C 1913363
 
7.8%
N 1788504
 
7.2%
T 1677251
 
6.8%
M 1644611
 
6.7%
_ 1644611
 
6.7%
O 1119582
 
4.5%
Other values (6) 2195793
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24672784
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 5070530
20.6%
I 2899700
11.8%
R 2761479
11.2%
E 1957360
 
7.9%
C 1913363
 
7.8%
N 1788504
 
7.2%
T 1677251
 
6.8%
M 1644611
 
6.7%
_ 1644611
 
6.7%
O 1119582
 
4.5%
Other values (6) 2195793
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24672784
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 5070530
20.6%
I 2899700
11.8%
R 2761479
11.2%
E 1957360
 
7.9%
C 1913363
 
7.8%
N 1788504
 
7.2%
T 1677251
 
6.8%
M 1644611
 
6.7%
_ 1644611
 
6.7%
O 1119582
 
4.5%
Other values (6) 2195793
8.9%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size18.0 MiB
2024-12-30T17:04:00.962004image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters30698980
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 2361460
100.0%
2024-12-30T17:04:01.068332image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 4722920
15.4%
A 4722920
15.4%
N 2361460
7.7%
O 2361460
7.7%
T 2361460
7.7%
H 2361460
7.7%
_ 2361460
7.7%
M 2361460
7.7%
E 2361460
7.7%
I 2361460
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30698980
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 4722920
15.4%
A 4722920
15.4%
N 2361460
7.7%
O 2361460
7.7%
T 2361460
7.7%
H 2361460
7.7%
_ 2361460
7.7%
M 2361460
7.7%
E 2361460
7.7%
I 2361460
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30698980
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 4722920
15.4%
A 4722920
15.4%
N 2361460
7.7%
O 2361460
7.7%
T 2361460
7.7%
H 2361460
7.7%
_ 2361460
7.7%
M 2361460
7.7%
E 2361460
7.7%
I 2361460
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30698980
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 4722920
15.4%
A 4722920
15.4%
N 2361460
7.7%
O 2361460
7.7%
T 2361460
7.7%
H 2361460
7.7%
_ 2361460
7.7%
M 2361460
7.7%
E 2361460
7.7%
I 2361460
7.7%

level0Gid
Text

Missing 

Distinct237
Distinct (%)0.1%
Missing1911127
Missing (%)80.9%
Memory size18.0 MiB
2024-12-30T17:04:01.224571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1351014
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowUSA
2nd rowUSA
3rd rowUSA
4th rowUSA
5th rowCRI
ValueCountFrequency (%)
usa 191983
42.6%
ven 20119
 
4.5%
bra 20003
 
4.4%
guy 18195
 
4.0%
mex 16475
 
3.7%
ecu 12944
 
2.9%
per 9844
 
2.2%
can 9240
 
2.1%
pan 6074
 
1.3%
bol 6000
 
1.3%
Other values (227) 139461
31.0%
2024-12-30T17:04:01.438738image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 260823
19.3%
U 244099
18.1%
S 209561
15.5%
E 69205
 
5.1%
N 67199
 
5.0%
R 56601
 
4.2%
C 47627
 
3.5%
G 44616
 
3.3%
M 43317
 
3.2%
B 38463
 
2.8%
Other values (20) 269503
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1351014
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 260823
19.3%
U 244099
18.1%
S 209561
15.5%
E 69205
 
5.1%
N 67199
 
5.0%
R 56601
 
4.2%
C 47627
 
3.5%
G 44616
 
3.3%
M 43317
 
3.2%
B 38463
 
2.8%
Other values (20) 269503
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1351014
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 260823
19.3%
U 244099
18.1%
S 209561
15.5%
E 69205
 
5.1%
N 67199
 
5.0%
R 56601
 
4.2%
C 47627
 
3.5%
G 44616
 
3.3%
M 43317
 
3.2%
B 38463
 
2.8%
Other values (20) 269503
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1351014
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 260823
19.3%
U 244099
18.1%
S 209561
15.5%
E 69205
 
5.1%
N 67199
 
5.0%
R 56601
 
4.2%
C 47627
 
3.5%
G 44616
 
3.3%
M 43317
 
3.2%
B 38463
 
2.8%
Other values (20) 269503
19.9%

level0Name
Text

Missing 

Distinct237
Distinct (%)0.1%
Missing1911127
Missing (%)80.9%
Memory size18.0 MiB
2024-12-30T17:04:01.575550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length30
Mean length10.17424024
Min length4

Characters and Unicode

Total characters4581847
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowUnited States
3rd rowUnited States
4th rowUnited States
5th rowCosta Rica
ValueCountFrequency (%)
united 193094
27.7%
states 192247
27.6%
venezuela 20119
 
2.9%
brazil 20003
 
2.9%
guyana 18195
 
2.6%
méxico 16475
 
2.4%
ecuador 12944
 
1.9%
peru 9844
 
1.4%
canada 9240
 
1.3%
french 6658
 
1.0%
Other values (276) 197266
28.3%
2024-12-30T17:04:01.780330image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 615456
13.4%
a 532048
11.6%
e 528246
11.5%
i 371986
 
8.1%
n 350657
 
7.7%
245747
 
5.4%
d 242883
 
5.3%
s 236258
 
5.2%
S 209349
 
4.6%
U 194325
 
4.2%
Other values (53) 1054892
23.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4581847
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 615456
13.4%
a 532048
11.6%
e 528246
11.5%
i 371986
 
8.1%
n 350657
 
7.7%
245747
 
5.4%
d 242883
 
5.3%
s 236258
 
5.2%
S 209349
 
4.6%
U 194325
 
4.2%
Other values (53) 1054892
23.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4581847
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 615456
13.4%
a 532048
11.6%
e 528246
11.5%
i 371986
 
8.1%
n 350657
 
7.7%
245747
 
5.4%
d 242883
 
5.3%
s 236258
 
5.2%
S 209349
 
4.6%
U 194325
 
4.2%
Other values (53) 1054892
23.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4581847
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 615456
13.4%
a 532048
11.6%
e 528246
11.5%
i 371986
 
8.1%
n 350657
 
7.7%
245747
 
5.4%
d 242883
 
5.3%
s 236258
 
5.2%
S 209349
 
4.6%
U 194325
 
4.2%
Other values (53) 1054892
23.0%

level1Gid
Text

Missing 

Distinct2568
Distinct (%)0.6%
Missing1912765
Missing (%)81.0%
Memory size18.0 MiB
2024-12-30T17:04:01.942710image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.5924961
Min length6

Characters and Unicode

Total characters3406753
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)0.1%

Sample

1st rowUSA.49_1
2nd rowUSA.20_1
3rd rowUSA.32_1
4th rowUSA.38_1
5th rowCRI.2_1
ValueCountFrequency (%)
usa.47_1 28132
 
6.3%
usa.21_1 17503
 
3.9%
usa.34_1 16052
 
3.6%
usa.5_1 12531
 
2.8%
usa.10_1 9880
 
2.2%
usa.49_1 6455
 
1.4%
ven.1_1 6336
 
1.4%
usa.39_1 6190
 
1.4%
usa.6_1 5820
 
1.3%
usa.9_1 5812
 
1.3%
Other values (2558) 333989
74.4%
2024-12-30T17:04:02.172744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 602899
17.7%
_ 448654
13.2%
. 446732
13.1%
A 259830
 
7.6%
U 243468
 
7.1%
S 209473
 
6.1%
2 119917
 
3.5%
4 112031
 
3.3%
3 88305
 
2.6%
E 69205
 
2.0%
Other values (28) 806239
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3406753
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 602899
17.7%
_ 448654
13.2%
. 446732
13.1%
A 259830
 
7.6%
U 243468
 
7.1%
S 209473
 
6.1%
2 119917
 
3.5%
4 112031
 
3.3%
3 88305
 
2.6%
E 69205
 
2.0%
Other values (28) 806239
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3406753
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 602899
17.7%
_ 448654
13.2%
. 446732
13.1%
A 259830
 
7.6%
U 243468
 
7.1%
S 209473
 
6.1%
2 119917
 
3.5%
4 112031
 
3.3%
3 88305
 
2.6%
E 69205
 
2.0%
Other values (28) 806239
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3406753
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 602899
17.7%
_ 448654
13.2%
. 446732
13.1%
A 259830
 
7.6%
U 243468
 
7.1%
S 209473
 
6.1%
2 119917
 
3.5%
4 112031
 
3.3%
3 88305
 
2.6%
E 69205
 
2.0%
Other values (28) 806239
23.7%

level1Name
Text

Missing 

Distinct2466
Distinct (%)0.5%
Missing1912765
Missing (%)81.0%
Memory size18.0 MiB
2024-12-30T17:04:02.305011image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length9.529788277
Min length3

Characters and Unicode

Total characters4276016
Distinct characters136
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique304 ?
Unique (%)0.1%

Sample

1st rowWest Virginia
2nd rowMaine
3rd rowNew Mexico
4th rowOregon
5th rowCartago
ValueCountFrequency (%)
virginia 34587
 
5.8%
carolina 18805
 
3.2%
maryland 17505
 
2.9%
north 16899
 
2.8%
california 14263
 
2.4%
amazonas 11119
 
1.9%
florida 9889
 
1.7%
new 9352
 
1.6%
columbia 7231
 
1.2%
west 7206
 
1.2%
Other values (2650) 446834
75.3%
2024-12-30T17:04:02.493806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 626722
14.7%
i 390317
 
9.1%
n 330354
 
7.7%
r 306970
 
7.2%
o 292322
 
6.8%
e 218622
 
5.1%
s 178051
 
4.2%
l 167995
 
3.9%
t 152746
 
3.6%
144990
 
3.4%
Other values (126) 1466927
34.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4276016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 626722
14.7%
i 390317
 
9.1%
n 330354
 
7.7%
r 306970
 
7.2%
o 292322
 
6.8%
e 218622
 
5.1%
s 178051
 
4.2%
l 167995
 
3.9%
t 152746
 
3.6%
144990
 
3.4%
Other values (126) 1466927
34.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4276016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 626722
14.7%
i 390317
 
9.1%
n 330354
 
7.7%
r 306970
 
7.2%
o 292322
 
6.8%
e 218622
 
5.1%
s 178051
 
4.2%
l 167995
 
3.9%
t 152746
 
3.6%
144990
 
3.4%
Other values (126) 1466927
34.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4276016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 626722
14.7%
i 390317
 
9.1%
n 330354
 
7.7%
r 306970
 
7.2%
o 292322
 
6.8%
e 218622
 
5.1%
s 178051
 
4.2%
l 167995
 
3.9%
t 152746
 
3.6%
144990
 
3.4%
Other values (126) 1466927
34.3%

level2Gid
Text

Missing 

Distinct14206
Distinct (%)3.3%
Missing1927745
Missing (%)81.6%
Memory size18.0 MiB
2024-12-30T17:04:02.643717image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.17989486
Min length7

Characters and Unicode

Total characters4415224
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3238 ?
Unique (%)0.7%

Sample

1st rowUSA.49.42_1
2nd rowUSA.20.10_1
3rd rowUSA.32.8_1
4th rowUSA.38.35_1
5th rowCRI.2.2_1
ValueCountFrequency (%)
usa.9.1_1 5812
 
1.3%
usa.21.15_1 4120
 
0.9%
usa.21.16_1 4057
 
0.9%
guy.8.8_1 3799
 
0.9%
usa.34.87_1 2754
 
0.6%
guy.2.8_1 2722
 
0.6%
guy.10.4_1 2607
 
0.6%
usa.47.40_1 2604
 
0.6%
usa.10.43_1 2474
 
0.6%
usa.47.50_1 2230
 
0.5%
Other values (14196) 400541
92.4%
2024-12-30T17:04:02.849456image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 865426
19.6%
1 701622
15.9%
_ 433720
9.8%
A 257502
 
5.8%
2 256721
 
5.8%
U 241816
 
5.5%
S 207671
 
4.7%
4 180295
 
4.1%
3 160264
 
3.6%
5 113447
 
2.6%
Other values (28) 996740
22.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4415224
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 865426
19.6%
1 701622
15.9%
_ 433720
9.8%
A 257502
 
5.8%
2 256721
 
5.8%
U 241816
 
5.5%
S 207671
 
4.7%
4 180295
 
4.1%
3 160264
 
3.6%
5 113447
 
2.6%
Other values (28) 996740
22.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4415224
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 865426
19.6%
1 701622
15.9%
_ 433720
9.8%
A 257502
 
5.8%
2 256721
 
5.8%
U 241816
 
5.5%
S 207671
 
4.7%
4 180295
 
4.1%
3 160264
 
3.6%
5 113447
 
2.6%
Other values (28) 996740
22.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4415224
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 865426
19.6%
1 701622
15.9%
_ 433720
9.8%
A 257502
 
5.8%
2 256721
 
5.8%
U 241816
 
5.5%
S 207671
 
4.7%
4 180295
 
4.1%
3 160264
 
3.6%
5 113447
 
2.6%
Other values (28) 996740
22.6%

level2Name
Text

Missing 

Distinct12303
Distinct (%)2.8%
Missing1927843
Missing (%)81.6%
Memory size18.0 MiB
2024-12-30T17:04:02.990824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length9.255439069
Min length1

Characters and Unicode

Total characters4013362
Distinct characters171
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2892 ?
Unique (%)0.7%

Sample

1st rowRandolph
2nd rowPenobscot
3rd rowDona Ana
4th rowWheeler
5th rowCartago
ValueCountFrequency (%)
of 16654
 
2.7%
rest 9994
 
1.6%
region 9986
 
1.6%
san 8897
 
1.4%
de 7619
 
1.2%
columbia 6006
 
1.0%
district 5938
 
1.0%
prince 5814
 
0.9%
montgomery 5411
 
0.9%
4736
 
0.8%
Other values (12308) 538339
86.9%
2024-12-30T17:04:03.201585image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 472396
 
11.8%
o 308144
 
7.7%
e 303212
 
7.6%
n 287417
 
7.2%
i 252179
 
6.3%
r 237395
 
5.9%
185772
 
4.6%
t 161195
 
4.0%
l 160373
 
4.0%
s 140990
 
3.5%
Other values (161) 1504289
37.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4013362
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 472396
 
11.8%
o 308144
 
7.7%
e 303212
 
7.6%
n 287417
 
7.2%
i 252179
 
6.3%
r 237395
 
5.9%
185772
 
4.6%
t 161195
 
4.0%
l 160373
 
4.0%
s 140990
 
3.5%
Other values (161) 1504289
37.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4013362
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 472396
 
11.8%
o 308144
 
7.7%
e 303212
 
7.6%
n 287417
 
7.2%
i 252179
 
6.3%
r 237395
 
5.9%
185772
 
4.6%
t 161195
 
4.0%
l 160373
 
4.0%
s 140990
 
3.5%
Other values (161) 1504289
37.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4013362
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 472396
 
11.8%
o 308144
 
7.7%
e 303212
 
7.6%
n 287417
 
7.2%
i 252179
 
6.3%
r 237395
 
5.9%
185772
 
4.6%
t 161195
 
4.0%
l 160373
 
4.0%
s 140990
 
3.5%
Other values (161) 1504289
37.5%

level3Gid
Text

Missing 

Distinct8199
Distinct (%)8.0%
Missing2259566
Missing (%)95.7%
Memory size18.0 MiB
2024-12-30T17:04:03.331128image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length14
Mean length11.77915387
Min length11

Characters and Unicode

Total characters1200284
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2818 ?
Unique (%)2.8%

Sample

1st rowCRI.2.2.4_1
2nd rowIND.19.16.3_1
3rd rowCHN.30.7.7_1
4th rowCRI.7.10.3_1
5th rowRUS.61.13.1_1
ValueCountFrequency (%)
can.13.1.35_1 1996
 
2.0%
per.18.3.4_1 1086
 
1.1%
per.8.9.1_1 918
 
0.9%
per.1.4.3_1 869
 
0.9%
pan.4.2.4_1 817
 
0.8%
pan.4.2.6_1 809
 
0.8%
mdg.2.1.5_1 704
 
0.7%
cri.5.2.1_1 568
 
0.6%
mdg.6.2.3_1 521
 
0.5%
per.18.1.1_1 500
 
0.5%
Other values (8189) 93111
91.4%
2024-12-30T17:04:03.516596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 305697
25.5%
1 204675
17.1%
_ 101899
 
8.5%
2 69195
 
5.8%
3 45152
 
3.8%
4 42438
 
3.5%
C 35435
 
3.0%
E 30901
 
2.6%
5 30354
 
2.5%
A 29431
 
2.5%
Other values (25) 305107
25.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1200284
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 305697
25.5%
1 204675
17.1%
_ 101899
 
8.5%
2 69195
 
5.8%
3 45152
 
3.8%
4 42438
 
3.5%
C 35435
 
3.0%
E 30901
 
2.6%
5 30354
 
2.5%
A 29431
 
2.5%
Other values (25) 305107
25.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1200284
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 305697
25.5%
1 204675
17.1%
_ 101899
 
8.5%
2 69195
 
5.8%
3 45152
 
3.8%
4 42438
 
3.5%
C 35435
 
3.0%
E 30901
 
2.6%
5 30354
 
2.5%
A 29431
 
2.5%
Other values (25) 305107
25.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1200284
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 305697
25.5%
1 204675
17.1%
_ 101899
 
8.5%
2 69195
 
5.8%
3 45152
 
3.8%
4 42438
 
3.5%
C 35435
 
3.0%
E 30901
 
2.6%
5 30354
 
2.5%
A 29431
 
2.5%
Other values (25) 305107
25.4%

level3Name
Text

Missing 

Distinct7682
Distinct (%)7.6%
Missing2260777
Missing (%)95.7%
Memory size18.0 MiB
2024-12-30T17:04:03.669530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length10.13206142
Min length2

Characters and Unicode

Total characters1020177
Distinct characters138
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2587 ?
Unique (%)2.6%

Sample

1st rowDulce Nombre
2nd rowKukshi
3rd rowLunan
4th rowSan Pedro
5th rowBan Luang
ValueCountFrequency (%)
unorganized 3367
 
2.2%
san 3200
 
2.1%
de 3074
 
2.0%
yukon 1996
 
1.3%
el 1944
 
1.2%
santa 1489
 
1.0%
la 1389
 
0.9%
rio 1264
 
0.8%
no 1168
 
0.8%
tambopata 1086
 
0.7%
Other values (7994) 135620
87.2%
2024-12-30T17:04:03.890830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 141794
 
13.9%
o 73803
 
7.2%
n 72304
 
7.1%
i 64580
 
6.3%
e 60131
 
5.9%
54909
 
5.4%
r 52653
 
5.2%
u 39382
 
3.9%
l 35764
 
3.5%
t 33716
 
3.3%
Other values (128) 391141
38.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1020177
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 141794
 
13.9%
o 73803
 
7.2%
n 72304
 
7.1%
i 64580
 
6.3%
e 60131
 
5.9%
54909
 
5.4%
r 52653
 
5.2%
u 39382
 
3.9%
l 35764
 
3.5%
t 33716
 
3.3%
Other values (128) 391141
38.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1020177
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 141794
 
13.9%
o 73803
 
7.2%
n 72304
 
7.1%
i 64580
 
6.3%
e 60131
 
5.9%
54909
 
5.4%
r 52653
 
5.2%
u 39382
 
3.9%
l 35764
 
3.5%
t 33716
 
3.3%
Other values (128) 391141
38.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1020177
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 141794
 
13.9%
o 73803
 
7.2%
n 72304
 
7.1%
i 64580
 
6.3%
e 60131
 
5.9%
54909
 
5.4%
r 52653
 
5.2%
u 39382
 
3.9%
l 35764
 
3.5%
t 33716
 
3.3%
Other values (128) 391141
38.3%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing383088
Missing (%)16.2%
Memory size18.0 MiB
2024-12-30T17:04:03.943872image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters3956754
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNE
2nd rowNE
3rd rowLC
4th rowNE
5th rowNE
ValueCountFrequency (%)
ne 1310250
66.2%
lc 593364
30.0%
vu 24743
 
1.3%
nt 19503
 
1.0%
en 12442
 
0.6%
dd 10871
 
0.5%
cr 6368
 
0.3%
ex 663
 
< 0.1%
ew 173
 
< 0.1%
2024-12-30T17:04:04.035947image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1342195
33.9%
E 1323528
33.4%
C 599732
15.2%
L 593364
15.0%
V 24743
 
0.6%
U 24743
 
0.6%
D 21742
 
0.5%
T 19503
 
0.5%
R 6368
 
0.2%
X 663
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3956754
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1342195
33.9%
E 1323528
33.4%
C 599732
15.2%
L 593364
15.0%
V 24743
 
0.6%
U 24743
 
0.6%
D 21742
 
0.5%
T 19503
 
0.5%
R 6368
 
0.2%
X 663
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3956754
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1342195
33.9%
E 1323528
33.4%
C 599732
15.2%
L 593364
15.0%
V 24743
 
0.6%
U 24743
 
0.6%
D 21742
 
0.5%
T 19503
 
0.5%
R 6368
 
0.2%
X 663
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3956754
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1342195
33.9%
E 1323528
33.4%
C 599732
15.2%
L 593364
15.0%
V 24743
 
0.6%
U 24743
 
0.6%
D 21742
 
0.5%
T 19503
 
0.5%
R 6368
 
0.2%
X 663
 
< 0.1%